This is a table of type bigram and their frequencies. Use it to search & browse the list to learn more about your study carrel.
bigram | frequency |
---|---|
posted january | 1337 |
copyright holder | 1337 |
version posted | 1337 |
biorxiv preprint | 1337 |
author funder | 1337 |
peer review | 1329 |
preprint https | 1291 |
preprintthis version | 1250 |
et al | 1217 |
org licenses | 879 |
granted biorxiv | 877 |
rights reserved | 449 |
reuse allowed | 448 |
allowed without | 448 |
without permission | 448 |
international licenseavailable | 435 |
international licensemade | 355 |
licensemade available | 355 |
cell lines | 281 |
cell types | 218 |
cell type | 202 |
seq data | 189 |
gene expression | 166 |
cell line | 119 |
supplementary table | 109 |
scalar curvature | 108 |
kdl qaa | 107 |
qaa http | 106 |
single cell | 105 |
made available | 103 |
nucleic acids | 100 |
hbv integration | 97 |
scalar curvatures | 95 |
deep learning | 93 |
methods section | 92 |
kdl gtt | 92 |
com eqnedit | 92 |
gtt http | 91 |
kdl jg | 89 |
cancer types | 83 |
editing frequency | 82 |
international licensea | 78 |
notthis version | 78 |
licensea certified | 78 |
kdl lmi | 75 |
see methods | 72 |
kdl bijvc | 71 |
bijvc http | 70 |
triplex motifs | 69 |
ps ta | 69 |
kdl vecw | 68 |
vecw http | 67 |
au content | 66 |
methylation array | 66 |
kdl ahwg | 66 |
see figure | 66 |
amino acid | 66 |
cell rna | 65 |
rna editing | 64 |
cancer type | 64 |
ahwg http | 64 |
acids res | 63 |
cancer cell | 63 |
expression levels | 63 |
supplementary figure | 62 |
machine learning | 62 |
copy number | 62 |
editing sites | 61 |
secondary structure | 61 |
kdl udus | 58 |
kdl wfrst | 58 |
udus http | 57 |
expression profiles | 56 |
wfrst http | 56 |
kdl xp | 56 |
gene pairs | 55 |
mammalian methylation | 55 |
data fig | 54 |
kdl sj | 54 |
extended data | 53 |
training data | 52 |
ccn scores | 50 |
kdl isag | 50 |
essential genes | 49 |
isag http | 49 |
sequencing data | 48 |
edited cytidine | 47 |
ccn score | 47 |
data sets | 46 |
time min | 46 |
total number | 46 |
host prediction | 45 |
least one | 45 |
pearson correlation | 45 |
image patches | 45 |
em maps | 44 |
dna methylation | 43 |
acids research | 43 |
epithelial cells | 43 |
expression data | 43 |
integration sequences | 41 |
fold change | 41 |
integration sites | 41 |
supplementary fig | 41 |
rienrich seq | 41 |
stat activation | 39 |
enrich seq | 39 |
bulk rna | 39 |
end genes | 39 |
polya selection | 38 |
clustering methods | 38 |
dimer bound | 38 |
homo sapiens | 38 |
read pairs | 37 |
mooring sequence | 37 |
mutual information | 37 |
cell division | 37 |
klein bottle | 37 |
breast cancer | 36 |
valid read | 35 |
test set | 35 |
wavelet analysis | 35 |
biological replicates | 35 |
data set | 34 |
predicted atus | 34 |
neighborhood sizes | 34 |
cell data | 34 |
supplemental figure | 34 |
stat phosphorylation | 33 |
publicly available | 33 |
plos one | 33 |
maximal atu | 32 |
general classification | 32 |
mathematical models | 32 |
vjim http | 32 |
kdl vjim | 32 |
data analysis | 32 |
across different | 32 |
human genome | 31 |
neural network | 31 |
covid risk | 31 |
selection gse | 31 |
subtype classification | 31 |
risk factors | 31 |
bias rate | 31 |
cell surface | 30 |
cancer models | 30 |
batch correction | 30 |
wavelet power | 30 |
allele frequency | 30 |
barcode sequences | 30 |
expression level | 30 |
variant calling | 30 |
technical replicates | 29 |
lung cancer | 29 |
ovarian cancer | 29 |
image patch | 29 |
random forest | 29 |
amino acids | 29 |
general ccn | 28 |
min ps | 28 |
genomic features | 28 |
rna sequencing | 28 |
risk factor | 28 |
mass spectrometry | 28 |
indel errors | 28 |
reference genome | 28 |
tumor transcriptome | 28 |
mrna editing | 28 |
beta diversity | 27 |
per unit | 27 |
tumor type | 27 |
tumor types | 27 |
ground truth | 27 |
ms spectra | 27 |
org content | 26 |
host pairs | 26 |
gene essentiality | 26 |
neural networks | 26 |
whole genome | 26 |
showing mean | 26 |
two technical | 26 |
manifold dimension | 26 |
tcga pan | 26 |
mock mock | 26 |
new infections | 26 |
read counts | 25 |
std dev | 25 |
mammalian array | 25 |
oligonucleotide compositions | 25 |
return plots | 25 |
artificial multiplets | 25 |
vntr loci | 25 |
expressed genes | 25 |
multiple sclerosis | 25 |
regulatory sequence | 25 |
figure shows | 25 |
health care | 25 |
average mutual | 25 |
heterotypic multiplets | 25 |
mrna transcripts | 24 |
fdissim indices | 24 |
different cell | 24 |
principal components | 24 |
environmental distance | 24 |
drug prescriptions | 24 |
homotypic multiplets | 24 |
dna sequences | 24 |
pan cancer | 24 |
innate immune | 24 |
supp tab | 24 |
unit increments | 24 |
spike protein | 24 |
epic array | 24 |
electronic health | 23 |
enrichment analysis | 23 |
hla alleles | 23 |
stop codon | 23 |
refseq annotation | 23 |
prediction accuracy | 23 |
gene induction | 23 |
integrated datasets | 23 |
transcriptome data | 23 |
mouse brain | 23 |
competing interests | 23 |
favorable interactions | 23 |
type specific | 23 |
motion estimation | 23 |
clique sum | 23 |
new york | 23 |
nature methods | 23 |
downstream sequence | 22 |
correlation coefficient | 22 |
processing methods | 22 |
vinyl sulfone | 22 |
altering variants | 22 |
edwards et | 22 |
ambient space | 22 |
capsule network | 22 |
galiez et | 22 |
url https | 22 |
similarity metrics | 22 |
presence absence | 22 |
aware model | 22 |
wide range | 22 |
length scale | 22 |
default parameters | 22 |
standard deviation | 22 |
acute respiratory | 22 |
gene annotations | 21 |
supervised approach | 21 |
performed using | 21 |
cancer genome | 21 |
statistical software | 21 |
large number | 21 |
read depth | 21 |
mitochondrial dna | 21 |
rsubread annotation | 21 |
three biological | 21 |
mathematical model | 21 |
atu clusters | 21 |
directional changes | 21 |
absence data | 21 |
developmental time | 21 |
supp fig | 21 |
quadruplex motifs | 21 |
kdl xpakk | 21 |
systems biology | 21 |
cell similarities | 21 |
expression profile | 21 |
care records | 21 |
optical flow | 21 |
five cancer | 21 |
principal component | 21 |
spatial transcriptomics | 21 |
also found | 21 |
supplementary file | 21 |
consensus sequences | 20 |
nature biotechnology | 20 |
tumor suppressor | 20 |
gwas enrichment | 20 |
seq datasets | 20 |
prescription events | 20 |
los angeles | 20 |
differentially expressed | 20 |
disease modules | 20 |
virus genome | 20 |
uniformly sampled | 20 |
fi time | 20 |
splice variant | 20 |
prediction performance | 20 |
variant window | 20 |
differential geometry | 20 |
bronchial epithelial | 20 |
genome sequencing | 20 |
seq classifier | 20 |
training set | 20 |
data using | 19 |
experimental data | 19 |
population information | 19 |
ensembl annotation | 19 |
marker genes | 19 |
author contributions | 19 |
splice altering | 19 |
live cell | 19 |
bmc bioinformatics | 19 |
common essential | 19 |
dna barcode | 19 |
genome biol | 19 |
first prescription | 19 |
de novo | 19 |
xpakk http | 19 |
calibration data | 19 |
quality control | 19 |
immune responses | 19 |
integrated dataset | 19 |
similarity learning | 19 |
strain measures | 19 |
sequence alignment | 19 |
nat methods | 19 |
loss function | 19 |
phosphorylation kinetics | 19 |
functional genomics | 19 |
host species | 19 |
even though | 18 |
euclidean distance | 18 |
respiratory syndrome | 18 |
combat qn | 18 |
type clustering | 18 |
sample sample | 18 |
fractional error | 18 |
attention intensive | 18 |
browser brain | 18 |
taken together | 18 |
atom difference | 18 |
microarray data | 18 |
variable genes | 18 |
differential expression | 18 |
prescription event | 18 |
different types | 18 |
storage browser | 18 |
base content | 18 |
false positives | 18 |
ubiquitination sites | 18 |
rpe cells | 18 |
stop codons | 18 |
two communities | 18 |
public research | 18 |
binding sites | 18 |
deletion breakpoints | 18 |
data type | 18 |
data availability | 18 |
gse sars | 18 |
refseq annotations | 18 |
negative class | 18 |
com storage | 18 |
two cytokines | 17 |
variant calls | 17 |
south korea | 17 |
stat stat | 17 |
ta bl | 17 |
batch effects | 17 |
scrnaseq datasets | 17 |
single cells | 17 |
com work | 17 |
based methods | 17 |
across samples | 17 |
open source | 17 |
spike ace | 17 |
bl et | 17 |
acad sci | 17 |
gene annotation | 17 |
consensus sequence | 17 |
three annotations | 17 |
per cell | 17 |
ai https | 17 |
intrinsic curvature | 17 |
sequence data | 17 |
curvatures computed | 17 |
editing targets | 17 |
vinyl sulfones | 17 |
overlapping cell | 17 |
alternative polyadenylation | 17 |
preprint http | 17 |
genome sequences | 17 |
natl acad | 17 |
functional diversity | 17 |
clinical events | 17 |
fi ps | 17 |
decision threshold | 17 |
type diabetes | 17 |
zero scalar | 17 |
genome biology | 17 |
gene sets | 17 |
work bibliography | 17 |
power spectrum | 17 |
read count | 17 |
significantly enriched | 17 |
sequence motif | 17 |
two molecules | 17 |
nature communications | 17 |
healthy controls | 17 |
web server | 17 |
cell divisions | 17 |
effects identify | 16 |
severe acute | 16 |
em density | 16 |
also used | 16 |
mr motifs | 16 |
calculated using | 16 |
molecular biology | 16 |
power plot | 16 |
apob rna | 16 |
specific expression | 16 |
cell populations | 16 |
supplementary data | 16 |
bivariate wavelet | 16 |
phosphorylated stat | 16 |
widely used | 16 |
patch dataset | 16 |
mer counts | 16 |
bibliography http | 16 |
tumor transcriptomes | 16 |
source code | 16 |
grn status | 16 |
three different | 16 |
data generated | 16 |
computed scalar | 16 |
interacting phage | 16 |
computed using | 16 |
two datasets | 16 |
ccn classifier | 16 |
clinical data | 16 |
learning model | 16 |
transcriptomic data | 16 |
generation sequencing | 16 |
suppressor gene | 16 |
sample size | 16 |
represent cancer | 16 |
log nm | 16 |
division events | 16 |
allele frequencies | 15 |
neighborhood size | 15 |
cell differentiation | 15 |
analysing drug | 15 |
sle patients | 15 |
model selection | 15 |
component analysis | 15 |
ncbi refseq | 15 |
ring systems | 15 |
based approach | 15 |
prop gender | 15 |
ami gender | 15 |
high quality | 15 |
two different | 15 |
read distribution | 15 |
human bronchial | 15 |
downstream analyses | 15 |
false negatives | 15 |
cancer res | 15 |
classification profiles | 15 |
tumour cells | 15 |
different cancer | 15 |
deep neural | 15 |
generalized tradidiss | 15 |
expression datasets | 15 |
base composition | 15 |
false positive | 15 |
ms ms | 15 |
based dissimilarity | 15 |
biol chem | 15 |
cas screens | 15 |
balf samples | 15 |
package version | 15 |
seq rienrich | 15 |
nature reviews | 15 |
cysteine proteases | 15 |
mtdna deletions | 15 |
columns represent | 15 |
debar package | 15 |
ligand subgroups | 15 |
chain path | 15 |
cells infected | 15 |
human population | 15 |
genome atlas | 15 |
hydrogen bond | 15 |
human ace | 15 |
base pairs | 15 |
ifnl sars | 14 |
raw data | 14 |
pqa score | 14 |
beltrami operator | 14 |
segment cn | 14 |
computer science | 14 |
statistically significant | 14 |
second fundamental | 14 |
nsclc cell | 14 |
sustained stat | 14 |
supplementary figures | 14 |
relative abundances | 14 |
network analysis | 14 |
spatial spots | 14 |
ddgbind values | 14 |
lagged data | 14 |
dissimilarity indices | 14 |
scientific reports | 14 |
debar pipeline | 14 |
transcriptomics data | 14 |
regression model | 14 |
immune system | 14 |
cancer research | 14 |
wild type | 14 |
entity recognition | 14 |
vntr length | 14 |
cell marker | 14 |
similarity matrix | 14 |
bacterial genomes | 14 |
time series | 14 |
intergenic region | 14 |
chromatin state | 14 |
mri data | 14 |
convolutional neural | 14 |
low percent | 14 |
perfect matching | 14 |
fundamental form | 14 |
cell proportions | 14 |
cn values | 14 |
lines indicate | 14 |
therapydf testtherapydf | 14 |
pstat pstat | 14 |
chen et | 14 |
dependent changes | 14 |
cell carcinoma | 14 |
density maps | 14 |
corresponding author | 14 |
mutant nsclc | 14 |
transcriptional fidelity | 14 |
proc natl | 14 |
cytokine signaling | 14 |
length scales | 14 |
de bruijn | 14 |
recurrently disrupted | 14 |
also made | 14 |
univariate wavelet | 14 |
sequence match | 14 |
methylation levels | 14 |
read pair | 14 |
intronic variants | 14 |
host genomes | 14 |
correlation coefficients | 14 |
atom differences | 14 |
measurement noise | 14 |
fo ld | 14 |
th percentile | 14 |
moi sars | 14 |
generated using | 14 |
allowed us | 14 |
true value | 14 |
module genes | 14 |
gse mock | 13 |
gene pair | 13 |
subclonal segments | 13 |
input features | 13 |
single gene | 13 |
embedding dimension | 13 |
main text | 13 |
entry mechanisms | 13 |
frequently recurring | 13 |
flow cytometry | 13 |
strain analysis | 13 |
cysteine protease | 13 |
human reference | 13 |
unfavorable interactions | 13 |
human viruses | 13 |
ubiquitination site | 13 |
pairs per | 13 |
rows correspond | 13 |
acid sequence | 13 |
contributed equally | 13 |
healthy control | 13 |
experimental maps | 13 |
developmental biology | 13 |
sequence length | 13 |
network optimization | 13 |
sequencing depth | 13 |
junctions extract | 13 |
dr motifs | 13 |
chromatin accessibility | 13 |
tumor samples | 13 |
dimensional manifold | 13 |
tandem repeat | 13 |
seq quantification | 13 |
true proportions | 13 |
bulk data | 13 |
pep trpm | 13 |
syndrome coronavirus | 13 |
srs reads | 13 |
classification scores | 13 |
binding proteins | 13 |
relative nmi | 13 |
nuclear norm | 13 |
shading corresponds | 13 |
protein ubiquitination | 13 |
spectral density | 13 |
apob mrna | 13 |
recurring genes | 13 |
effect size | 13 |
scatter plot | 13 |
fold cross | 13 |
evaluated using | 13 |
complex tissues | 13 |
cpg island | 13 |
type classification | 13 |
cancer cells | 13 |
clinical trials | 13 |
use case | 13 |
na na | 13 |
read mapping | 13 |
significantly higher | 13 |
ve ro | 13 |
uniform read | 13 |
riemannian curvature | 13 |
shapley values | 13 |
type proportions | 13 |
deephbv model | 13 |
available data | 13 |
downstream analysis | 13 |
randomly selected | 13 |
severe covid | 13 |
editing site | 13 |
qn pc | 13 |
per sample | 13 |
much higher | 13 |
environmental filtering | 13 |
using different | 13 |
attention weight | 13 |
expression value | 13 |
mol biol | 12 |
common essentials | 12 |
across species | 12 |
ir motifs | 12 |
data used | 12 |
cancer dependency | 12 |
host predictions | 12 |
primary human | 12 |
cc license | 12 |
attention mechanism | 12 |
phase difference | 12 |
normalization methods | 12 |
atu prediction | 12 |
significant associations | 12 |
file containing | 12 |
lung samples | 12 |
subtype classifiers | 12 |
curvature estimation | 12 |
closely related | 12 |
government work | 12 |
technical errors | 12 |
classification general | 12 |
differentially essential | 12 |
hepatocellular carcinoma | 12 |
reference transcriptome | 12 |
cell biology | 12 |
com single | 12 |
stat via | 12 |
within cells | 12 |
titration monotonicity | 12 |
mapping rates | 12 |
general tumor | 12 |
resistant biomolecules | 12 |
myocardial strain | 12 |
posterior distributions | 12 |
per nucleus | 12 |
host sequences | 12 |
log fold | 12 |
authors contributed | 12 |
fi pstat | 12 |
highly conserved | 12 |
see figures | 12 |
cell models | 12 |
gene ontology | 12 |
pmc articles | 12 |
reads per | 12 |
scaling factor | 12 |
gene region | 12 |
protein localization | 12 |
run run | 12 |
tcga cohort | 12 |
gene regulatory | 12 |
clinicaldf testclinicaldf | 12 |
intensive regions | 12 |
human epic | 12 |
cytokine receptor | 12 |
em map | 12 |
expression analysis | 12 |
accession number | 12 |
cancer category | 12 |
gender gender | 12 |
us government | 12 |
peripheral blood | 12 |
also observed | 12 |
small intestine | 12 |
bnwyax uh | 12 |
regulatory motif | 12 |
previous studies | 12 |
major arc | 12 |
text mining | 12 |
major cell | 12 |
intergenic regions | 12 |
gaussian noise | 12 |
expression values | 12 |
highly similar | 12 |
cellular origins | 12 |
relative abundance | 12 |
pstat via | 12 |
human pancreatic | 12 |
genetic dependencies | 12 |
electron microscopy | 12 |
ambient dimension | 12 |
furin site | 12 |
content early | 12 |
consensus modules | 12 |
base pair | 12 |
free tail | 12 |
cancer categories | 12 |
metabolomics data | 12 |
transcription factor | 12 |
editing frequencies | 12 |
squamous cell | 12 |
mrna transcript | 12 |
correction pipelines | 12 |
gene dependency | 12 |
pbmc samples | 12 |
splice site | 12 |
alternative splicing | 12 |
xgboost method | 12 |
regulatory networks | 12 |
environmental gradient | 12 |
edge annotation | 12 |
seq expression | 12 |
global network | 12 |
computational biology | 12 |
phase contrast | 12 |
expression profiling | 11 |
effective gene | 11 |
cancer institute | 11 |
splice junction | 11 |
ms data | 11 |
cardiac cycle | 11 |
see supplementary | 11 |
phage sequence | 11 |
free dna | 11 |
mammalian species | 11 |
atu cluster | 11 |
reconstruction loss | 11 |
university school | 11 |
genomic data | 11 |
differential motif | 11 |
cell segmentation | 11 |
linear regression | 11 |
proteomic changes | 11 |
cardiac motion | 11 |
motif usage | 11 |
box counting | 11 |
sequence similarity | 11 |
seq dataset | 11 |
validation strategy | 11 |
high levels | 11 |
code availability | 11 |
closest point | 11 |
metabarcode data | 11 |
alternate donor | 11 |
sequence coverage | 11 |
sequencing reads | 11 |
frequency variants | 11 |
truth set | 11 |
ucsc genome | 11 |
pstat levels | 11 |
supplementary information | 11 |
genome research | 11 |
washington university | 11 |
dependent genes | 11 |
divergent sequences | 11 |
gene lengths | 11 |
isotropic gaussian | 11 |
global length | 11 |
type specificity | 11 |
marker gene | 11 |
junctions annotate | 11 |
genomics data | 11 |
umap coordinates | 11 |
motion estimates | 11 |
vntr locus | 11 |
candidate formula | 11 |
limited number | 11 |
original dataset | 11 |
parameter set | 11 |
retention time | 11 |
nature genetics | 11 |
marker peaks | 11 |
deletion bps | 11 |
dependency map | 11 |
seq analysis | 11 |
elapsed month | 11 |
error rate | 11 |
nm ps | 11 |
specific signals | 11 |
untargeted metabolomics | 11 |
ccn classification | 11 |
operating characteristic | 11 |
phage genomes | 11 |
gene set | 11 |
usa department | 11 |
uniform distribution | 11 |
homology model | 11 |
genetic variants | 11 |
clustering analysis | 11 |
hq http | 11 |
variational autoencoder | 11 |
density map | 11 |
drug response | 11 |
cell lung | 11 |
degenerate bases | 11 |
specific deconvolution | 11 |
tf binding | 11 |
protein expression | 11 |
negative control | 11 |
infectious potential | 11 |
medcodelist headachecodes | 11 |
variants annotate | 11 |
trajectory data | 11 |
biomedical literature | 11 |
cell biol | 11 |
software package | 11 |
global optimization | 11 |
cell similarity | 11 |
forest classifier | 11 |
dna sequence | 11 |
empirical eigenvalues | 11 |
open access | 11 |
expression matrix | 11 |
human cells | 11 |
acid continuous | 11 |
authors declare | 11 |
differential essentiality | 10 |
power levels | 10 |
clonal segments | 10 |
single molecule | 10 |
normally distributed | 10 |
cell transcriptomics | 10 |
sample variability | 10 |
bnwyax wfsum | 10 |
species dissimilarities | 10 |
similarity relation | 10 |
binding motifs | 10 |
phage sequences | 10 |
host cells | 10 |
experimental tsss | 10 |
human tissues | 10 |
vntr regions | 10 |
bayesian inference | 10 |
ms spectrum | 10 |
width wrap | 10 |
taqman rt | 10 |
bronchoalveolar lavage | 10 |
functional dissimilarity | 10 |
nugent et | 10 |
shah et | 10 |
new cases | 10 |
two refseq | 10 |
vegetation science | 10 |
distinct atus | 10 |
synthetic lethality | 10 |
ns em | 10 |
model using | 10 |
association studies | 10 |
clinically relevant | 10 |
downregulated genes | 10 |
main stem | 10 |
virus genomes | 10 |
two nodes | 10 |
feature importance | 10 |
pathway enrichment | 10 |
cell proliferation | 10 |
date df | 10 |
receiver operating | 10 |
bnwyax eqqvf | 10 |
research allele | 10 |
big data | 10 |
gc content | 10 |
binary matrix | 10 |
found using | 10 |
cell clusters | 10 |
ace spike | 10 |
similar results | 10 |
based prediction | 10 |
importance scores | 10 |
results suggest | 10 |
linear model | 10 |
latent space | 10 |
rna polymerase | 10 |
complex diseases | 10 |
hierarchical clustering | 10 |
bottle embedding | 10 |
top scored | 10 |
regional strain | 10 |
drug reactions | 10 |
wide association | 10 |
epithelial sodium | 10 |
donor usage | 10 |
zzqk xjeg | 10 |
average power | 10 |
transcription factors | 10 |
cfdna samples | 10 |
expression patterns | 10 |
university press | 10 |
su br | 10 |
similarity network | 10 |
donor site | 10 |
complex systems | 10 |
pacbio hifi | 10 |
liquid biopsies | 10 |
figure legends | 10 |
novel junctions | 10 |
wt il | 10 |
cell cycle | 10 |
library preparation | 10 |
mol cell | 10 |
persson et | 10 |
normal direction | 10 |
sequences tcga | 10 |
dissimilarity measures | 10 |
sustained pstat | 10 |
stat response | 10 |
er motifs | 10 |
pdf https | 10 |
recent studies | 10 |
variants within | 10 |
pavoine ricotta | 10 |
louvain clustering | 10 |
model input | 10 |
individual nucleotides | 10 |
lowly expressed | 10 |
expression quantification | 10 |
protein sequence | 10 |
evaluation data | 10 |
mutation status | 10 |
relaxed matching | 10 |
natural language | 10 |
right side | 10 |
islet samples | 10 |
residue match | 10 |
pangenome graphs | 10 |
confidence interval | 10 |
ctd rpd | 10 |
relative subclonal | 10 |
fold induction | 10 |
em bl | 10 |
spectrometry phenomena | 10 |
mononuclear cells | 10 |
hidden markov | 10 |
zhang et | 10 |
barcode data | 10 |
therapeutic targets | 10 |
reference panel | 10 |
one sample | 10 |
pancreatic islets | 10 |
regulatory network | 10 |
based approaches | 10 |
image analysis | 10 |
re gu | 10 |
plot showing | 10 |
lavage fluid | 10 |
gene mrna | 10 |
ai ve | 10 |
per million | 10 |
two cell | 10 |
br ea | 10 |
bnwyax ezh | 10 |
time lags | 10 |
maximal il | 10 |
acceptor site | 10 |
blanc et | 10 |
cancer genes | 10 |
infection rates | 10 |
al iz | 10 |
cell clustering | 10 |
triplex package | 10 |
classification score | 10 |
bmc genomics | 10 |
joint periods | 10 |
genome browser | 10 |
function modules | 10 |
signaling pathways | 10 |
programming model | 10 |
bruijn graph | 10 |
secondary structures | 10 |
supplemental files | 10 |
accessibility profiles | 10 |
ensembl genes | 10 |
variant candidate | 10 |
six clades | 10 |
synthetic biology | 10 |
type clusters | 10 |
upregulated genes | 10 |
distance matrix | 9 |
nat immunol | 9 |
acid type | 9 |
bnwyax wm | 9 |
genome sequence | 9 |
dominant co | 9 |
count matrix | 9 |
inner sum | 9 |
higher proportion | 9 |
bnwyax shsw | 9 |
number alterations | 9 |
previous study | 9 |
cov strains | 9 |
index https | 9 |
cell rep | 9 |
ricotta et | 9 |
network fusion | 9 |
healthy subjects | 9 |
supplementary materials | 9 |
min score | 9 |
alveolar epithelial | 9 |
three datasets | 9 |
biological networks | 9 |
uniform sampling | 9 |
distance metrics | 9 |
exon skipping | 9 |
ci containing | 9 |
intrinsic coordinates | 9 |
chain probability | 9 |
feature vectors | 9 |
information content | 9 |
serous ovarian | 9 |
across cell | 9 |
bnwyax kxhhl | 9 |
odthp http | 9 |
candidate formulae | 9 |
national academy | 9 |
prior knowledge | 9 |
individual cells | 9 |
transcription units | 9 |
different gene | 9 |
rank position | 9 |
synthetic lethal | 9 |
exonic variants | 9 |
zzqk meu | 9 |
data bank | 9 |
junction region | 9 |
genes associated | 9 |
sampling time | 9 |
optimization problem | 9 |
stably expressing | 9 |
bnwyax karn | 9 |
ge ne | 9 |
blood samples | 9 |
amr sas | 9 |
immune response | 9 |
united kingdom | 9 |
international licensereview | 9 |
yang et | 9 |
theme bw | 9 |
human cancers | 9 |
identify genes | 9 |
mean expression | 9 |
factor dominance | 9 |
differentially methylated | 9 |
bnwyax odthp | 9 |
skipping event | 9 |
supplemental table | 9 |
emerging subclone | 9 |
important role | 9 |
genome res | 9 |
protein structure | 9 |
classification heatmap | 9 |
host cell | 9 |
average recall | 9 |
results showed | 9 |
extrinsic approach | 9 |
patient samples | 9 |
tumor dna | 9 |
candidate variant | 9 |
peerthis version | 9 |
female cell | 9 |
radial ess | 9 |
two types | 9 |
genomes project | 9 |
using deep | 9 |
logistic regression | 9 |
missing ref | 9 |
receptor assembly | 9 |
bnwyax assl | 9 |
com acnash | 9 |
time increment | 9 |
infinium ii | 9 |
driver within | 9 |
test sets | 9 |
dimensionality reduction | 9 |
genetic variation | 9 |
compound data | 9 |
afr eas | 9 |
similarity scores | 9 |
magnetic resonance | 9 |
vntr variation | 9 |
public health | 9 |
mapped reads | 9 |
consortium et | 9 |
human cancer | 9 |
patient derived | 9 |
blood mononuclear | 9 |
also showed | 9 |
reference manual | 9 |
induction log | 9 |
red marks | 9 |
blast results | 9 |
embryonic development | 9 |
bnwyax thhr | 9 |
bnwyax hbt | 9 |
training process | 9 |
ii gene | 9 |
cell expression | 9 |
type ii | 9 |
polar map | 9 |
associated diseases | 9 |
pcr test | 9 |
wei shi | 9 |
membrane protein | 9 |
bulk samples | 9 |
real time | 9 |
scanner repeatability | 9 |
linear transformation | 9 |
also calculated | 9 |
human islets | 9 |
visual inspection | 9 |
cleavage site | 9 |
irf protein | 9 |
relevant information | 9 |
johns hopkins | 9 |
positive class | 9 |
indel error | 9 |
chemotherapy prediction | 9 |
averaged across | 9 |
statistical significance | 9 |
time point | 9 |
small number | 9 |
cell distance | 9 |
probe sequences | 9 |
right panel | 9 |
different species | 9 |
eur amr | 9 |
cells stimulated | 9 |
df testtherapydf | 9 |
freely available | 9 |
probe sequence | 9 |
showed significant | 9 |
pol ii | 9 |
preprint mailto | 9 |
window size | 9 |
tandem repeats | 9 |
correction methods | 9 |
small cell | 9 |
cytoplasmic domain | 9 |
deletion formation | 9 |
please place | 9 |
international conference | 9 |
colorectal cancer | 9 |
model performance | 9 |
objective function | 9 |
bnwyax dwirj | 9 |
cancer biology | 9 |
given tcga | 9 |
rpe il | 9 |
red lines | 9 |
distance threshold | 9 |
hla genes | 9 |
mitochondrial disease | 9 |
nonhair cells | 9 |
th cells | 9 |
predicting response | 9 |
points uniformly | 9 |
pstat activation | 9 |
host interactions | 9 |
marks within | 9 |
ciliated cells | 9 |
visualisation package | 9 |
identified using | 9 |
probability map | 9 |
sas afr | 9 |
computer vision | 9 |
san francisco | 9 |
multiplet detection | 9 |
predicted main | 9 |
clustering method | 9 |
standard deviations | 9 |
maximum number | 9 |
rna viruses | 9 |
imd score | 9 |
surface receptor | 9 |
real bulk | 9 |
transcriptomic datasets | 9 |
input sequence | 9 |
sclapa provides | 9 |
cells indicate | 9 |
learning approach | 9 |
frequently contacted | 9 |
pbmc dataset | 9 |
pcr data | 9 |
bar plot | 9 |
hla allele | 9 |
go terms | 9 |
naturally occurring | 9 |
single nucleotide | 9 |
seq reads | 9 |
negative controls | 9 |
use cases | 9 |
structure determination | 9 |
target sequence | 9 |
cited dec | 9 |
quadratic regression | 9 |
reference sequences | 9 |
classification results | 9 |
subclonal tumour | 9 |
dependency scores | 9 |
showed favorable | 9 |
dna replication | 9 |
bnwyax iqbee | 9 |
different annotations | 9 |
language processing | 9 |
data processing | 9 |
default settings | 9 |
immune escape | 9 |
making use | 9 |
virus infection | 8 |
derived xenografts | 8 |
ezh http | 8 |
vntr lengths | 8 |
gbpm score | 8 |
ctd ndo | 8 |
learning rate | 8 |
org package | 8 |
predictive models | 8 |
bifqg http | 8 |
cov mrc | 8 |
old refseq | 8 |
baseline sample | 8 |
human samples | 8 |
initial annotation | 8 |
along mrna | 8 |
quantification accuracy | 8 |
network inference | 8 |
multiplets detected | 8 |
enriched around | 8 |
exon edge | 8 |
poisson distribution | 8 |
medical image | 8 |
scored models | 8 |
highly correlated | 8 |
spike glycoprotein | 8 |
dv glnexus | 8 |
zzqk ld | 8 |
pacific biosciences | 8 |
mbrave platform | 8 |
analytical eigenvalues | 8 |
prokaryotic genomes | 8 |
positive patients | 8 |
stat signaling | 8 |
pancreatic adenocarcinoma | 8 |
denoised sequences | 8 |
dctjj http | 8 |
infection efficiency | 8 |
bnwyax fenjn | 8 |
compound rna | 8 |
zzqk qisc | 8 |
xiamen university | 8 |
somatic mutations | 8 |
ctd jlne | 8 |
four datasets | 8 |
hla class | 8 |
research interests | 8 |
higher confidence | 8 |
similarity measures | 8 |
significant differences | 8 |
puerto rican | 8 |
conditionally essential | 8 |
novel junction | 8 |
point mutations | 8 |
van hateren | 8 |
gp il | 8 |
negative samples | 8 |
curtis index | 8 |
bnwyax htdux | 8 |
biologically relevant | 8 |
ii probes | 8 |
fc log | 8 |
lg unchanged | 8 |
cpg sites | 8 |
unbound cytoplasmic | 8 |
research cohort | 8 |
thermo scientific | 8 |
recent years | 8 |
previously described | 8 |
articles pmc | 8 |
human blood | 8 |
edge annotations | 8 |
wavelet coherence | 8 |
unknown general | 8 |
united states | 8 |
bnwyax jkgi | 8 |
ctd pjd | 8 |
embryo networks | 8 |
clustering results | 8 |
array probes | 8 |
com calculate | 8 |
ace cells | 8 |
methods based | 8 |
genomic positions | 8 |
significantly upregulated | 8 |
grade serous | 8 |
biosciences sequel | 8 |
community dissimilarity | 8 |
change log | 8 |
norm regularization | 8 |
inflammatory cytokines | 8 |
final model | 8 |
trait values | 8 |
shsw http | 8 |
patients prescribed | 8 |
learning algorithms | 8 |
curvature tensor | 8 |
cmaps algorithm | 8 |
tissue types | 8 |
lakshmanan et | 8 |
dashed red | 8 |
genes included | 8 |
new infection | 8 |
assl http | 8 |
data integration | 8 |
unmapped headers | 8 |
individual datasets | 8 |
genomic sequence | 8 |
abundance data | 8 |
bar graph | 8 |
identity thresholds | 8 |
among different | 8 |
infectious diseases | 8 |
analysis reveals | 8 |
vae architectures | 8 |
thhr http | 8 |
randomly sampled | 8 |
pooling module | 8 |
cryptosporidium parvum | 8 |
ethnic groups | 8 |
cprd gold | 8 |
atomic resolution | 8 |
convolutional layer | 8 |
positive samples | 8 |
ctd dguv | 8 |
trained using | 8 |
average number | 8 |
eqqvf http | 8 |
quadratic gradients | 8 |
supervised vae | 8 |
patient tumor | 8 |
bnwyax qc | 8 |
tissue cell | 8 |
ayqe http | 8 |
binding protein | 8 |
disrupted genes | 8 |
pcr primers | 8 |
bisulfite sequencing | 8 |
reactions involving | 8 |
ctd gs | 8 |
generation rna | 8 |
originally reported | 8 |
binding site | 8 |
table containing | 8 |
fold changes | 8 |
sapiens calu | 8 |
three times | 8 |
genetically engineered | 8 |
kxhhl http | 8 |
query sample | 8 |
sequel platform | 8 |
princeton university | 8 |
pdb entries | 8 |
extrinsic differential | 8 |
bnwyax ax | 8 |
bnwyax dctjj | 8 |
bnwyax ayqe | 8 |
input data | 8 |
ms use | 8 |
snp set | 8 |
enzymatic cleft | 8 |
variation across | 8 |
clinical event | 8 |
somatic variants | 8 |
classification performance | 8 |
bnwyax bifqg | 8 |
entry mechanism | 8 |
gradient length | 8 |
delta cells | 8 |
genetic diversity | 8 |
two groups | 8 |
esm http | 8 |
cohort dv | 8 |
gbpm analysis | 8 |
buj http | 8 |
iqbee http | 8 |
kgp cohort | 8 |
may also | 8 |
stat expression | 8 |
ctd lmbav | 8 |
cell reference | 8 |
common genes | 8 |
spike mutations | 8 |
per gene | 8 |
different sizes | 8 |
phage genome | 8 |
hidden subpopulations | 8 |
line encyclopedia | 8 |
partial shapley | 8 |
omics module | 8 |
extrinsic curvature | 8 |
aware models | 8 |
supervised learning | 8 |
strain rate | 8 |
negative feedback | 8 |
research network | 8 |
molecular mechanisms | 8 |
satellite glia | 8 |
wfsum http | 8 |
within bp | 8 |
hebert et | 8 |
reshuffled controls | 8 |
hong kong | 8 |
genomes sequenced | 8 |
ax xh | 8 |
cluster cells | 8 |
associated genes | 8 |
higher expression | 8 |
van der | 8 |
cohort kgp | 8 |
convolution kernels | 8 |
per day | 8 |
cells using | 8 |
cytokine responses | 8 |
virus entry | 8 |
detected multiplets | 8 |
glnexus opt | 8 |
line dpg | 8 |
specific gene | 8 |
mrna target | 8 |
mg ml | 8 |
host environment | 8 |
least two | 8 |
two principal | 8 |
rank assumption | 8 |
cancer data | 8 |
cell composition | 8 |
false discovery | 8 |
cd cd | 8 |
biological sequences | 8 |
hybrid motifs | 8 |
reviews genetics | 8 |
coi barcode | 8 |
specific genes | 8 |
pacbio sequel | 8 |
membrane fusion | 8 |
clustering algorithm | 8 |
data structure | 8 |
infecting viruses | 8 |
different conditions | 8 |
stem cells | 8 |
sample order | 8 |
previously reported | 8 |
nucleotides upstream | 8 |
quantification results | 8 |
ctd str | 8 |
median ccn | 8 |
type annotations | 8 |
prediction models | 8 |
drugcodelist amitriptylinecodes | 8 |
absolute subclonal | 8 |
ooj http | 8 |
top models | 7 |
mckerrow jh | 7 |
de bello | 7 |
cancer analysis | 7 |
parameter values | 7 |
apa isoforms | 7 |
elakatos liquidcna | 7 |
spectral clustering | 7 |
jkgi http | 7 |
normal distribution | 7 |
integrated genomic | 7 |
computational framework | 7 |
gene length | 7 |
nhbe cells | 7 |
computing scalar | 7 |
hopkins university | 7 |
using one | 7 |
factor binding | 7 |
highly expressed | 7 |
times greater | 7 |
cpg islands | 7 |
bottle embeddings | 7 |
state university | 7 |
struct biol | 7 |
acnash rdrugtrajectory | 7 |
image processing | 7 |
ncbi annotation | 7 |
based method | 7 |
cohort variants | 7 |
window length | 7 |
li et | 7 |
beta cell | 7 |
denoising pipeline | 7 |
potential splice | 7 |
resolution cryo | 7 |
subsite residues | 7 |
vntr sequences | 7 |
observational noise | 7 |
high fidelity | 7 |
data integrator | 7 |
rich medium | 7 |
future work | 7 |
st im | 7 |
cell ranger | 7 |
annotation choice | 7 |
also included | 7 |
chlorocebus sabaeus | 7 |
min min | 7 |
comprehensive resource | 7 |
subclonal cells | 7 |
human cell | 7 |
error reduction | 7 |
ctd haw | 7 |
using two | 7 |
dissimilarity index | 7 |
mouse models | 7 |
cprd data | 7 |
vae architecture | 7 |
bat sars | 7 |
flow rate | 7 |
prescription prodcode | 7 |
data points | 7 |
cytokine receptors | 7 |
beta cells | 7 |
convolutional filters | 7 |
tissue type | 7 |
using blast | 7 |
platform difference | 7 |
sodium channels | 7 |
dna barcodes | 7 |
fourier analysis | 7 |
alternate acceptor | 7 |
decision trees | 7 |
significant events | 7 |
zzqk srq | 7 |
binding domain | 7 |
le ng | 7 |
sequence logos | 7 |
four different | 7 |
modifier modules | 7 |
single variant | 7 |
distribution along | 7 |
coherence plot | 7 |
roadmap epigenomics | 7 |
rare cell | 7 |
present study | 7 |
degenerate base | 7 |
intensive sites | 7 |
ctd pj | 7 |
body mass | 7 |
model training | 7 |
mouse apobec | 7 |
ct iv | 7 |
methods using | 7 |
nat biotechnol | 7 |
genes recurrently | 7 |
peak annotation | 7 |
across cancer | 7 |
national institutes | 7 |
models using | 7 |
zzqk iwwe | 7 |
variation matrix | 7 |
cancer dependencies | 7 |
expected number | 7 |
zzqk uwiz | 7 |
rheumatoid arthritis | 7 |
fc lo | 7 |
signaling pathway | 7 |
royal society | 7 |
distribution function | 7 |
time points | 7 |
error rates | 7 |
across populations | 7 |
values across | 7 |
known metabolites | 7 |
subclonal evolution | 7 |
ensembl refseq | 7 |
contour lines | 7 |
high confidence | 7 |
cluster sizes | 7 |
driver mutations | 7 |
sokal sneath | 7 |
counts per | 7 |
inverse relationship | 7 |
bnwyax ymsj | 7 |
ms risk | 7 |
invasive carcinoma | 7 |
lx http | 7 |
bam file | 7 |
methods data | 7 |
length prediction | 7 |
crispr screens | 7 |
bnwyax xh | 7 |
less accurate | 7 |
data represents | 7 |
real data | 7 |
world data | 7 |
tyr motifs | 7 |
prescription records | 7 |
global strain | 7 |
results indicate | 7 |
rafsil rafsil | 7 |
disease associations | 7 |
human disease | 7 |
structure type | 7 |
ctd gyl | 7 |
noise level | 7 |
atlas research | 7 |
direct repeat | 7 |
tumour fraction | 7 |
computational methods | 7 |
synthetic bulk | 7 |
receptor complex | 7 |
set using | 7 |
ha ng | 7 |
significantly different | 7 |
ancestral sequences | 7 |
line mixtures | 7 |
microarray expression | 7 |
ari score | 7 |
native structure | 7 |
alignment quality | 7 |
three methods | 7 |
karn http | 7 |
us states | 7 |
see table | 7 |
expressing wt | 7 |
deepmm method | 7 |
germ cell | 7 |
different batch | 7 |
viral host | 7 |
web browser | 7 |
ctd jel | 7 |
calculate https | 7 |
novel metabolites | 7 |
retention times | 7 |
brain dataset | 7 |
short genes | 7 |
cancer gene | 7 |
frequency pretrained | 7 |
ng th | 7 |
disease types | 7 |
lines using | 7 |
different values | 7 |
learning models | 7 |
standard error | 7 |
htdux http | 7 |
red line | 7 |
nucleotides downstream | 7 |
json format | 7 |
active site | 7 |
much smaller | 7 |
sequences repeat | 7 |
discovery rate | 7 |
profile hidden | 7 |
line dpgs | 7 |
manually curated | 7 |
barcode region | 7 |
data collection | 7 |
practice research | 7 |
min time | 7 |
control sirna | 7 |
first two | 7 |
violin plots | 7 |
sparsity regularization | 7 |
reference sequence | 7 |
ctd jzyin | 7 |
ctd akii | 7 |
end gene | 7 |
corrections applied | 7 |
model based | 7 |
identify potential | 7 |
ctd yrlys | 7 |
average scalar | 7 |
numeric embryo | 7 |
positive control | 7 |
table shows | 7 |
cell entry | 7 |
sample sizes | 7 |
xh http | 7 |
analysis methods | 7 |
evaluated atus | 7 |
reveals genes | 7 |
ct io | 7 |
data distribution | 7 |
arbab et | 7 |
breast invasive | 7 |
messenger rna | 7 |
multiple samples | 7 |
gp ko | 7 |
dashed line | 7 |
ctd crk | 7 |
source repository | 7 |
mtdna deletion | 7 |
user interface | 7 |
modifier methods | 7 |
rate function | 7 |
additional information | 7 |
ctd eix | 7 |
splicing events | 7 |
ctd jmtrf | 7 |
across datasets | 7 |
known cancer | 7 |
distance metric | 7 |
specific prescription | 7 |
first step | 7 |
pretrained model | 7 |
netid algorithm | 7 |
clinical practice | 7 |
pj xm | 7 |
dwirj http | 7 |
allows us | 7 |
statistical tests | 7 |
truncated series | 7 |
dimensional manifolds | 7 |
severe illness | 7 |
targeted gene | 7 |
connected layers | 7 |
jlne http | 7 |
overall secondary | 7 |
viral genome | 7 |
data obtained | 7 |
ymsj http | 7 |
selected multiplets | 7 |
site prediction | 7 |
nat rev | 7 |
biological processes | 7 |
viral genomes | 7 |
circulating tumor | 7 |
feature data | 7 |
nat commun | 7 |
conditions like | 7 |
learning research | 7 |
average score | 7 |
long reads | 7 |
cancer genomics | 7 |
modeling non | 7 |
cell profiling | 7 |
null distribution | 7 |
bnwyax zwnw | 7 |
high number | 7 |
detect multiplets | 7 |
novel cell | 7 |
pdb id | 7 |
blast search | 7 |
see sec | 7 |
place fig | 7 |
mutagenic motifs | 7 |
plasma membrane | 7 |
specific grn | 7 |
sequences used | 7 |
converting enzyme | 7 |
distance fusion | 7 |
experimental ttss | 7 |
cell population | 7 |
dna motifs | 7 |
weighted sum | 7 |
epigenomics consortium | 7 |
intrinsic approach | 7 |
ctd jzbjy | 7 |
ambient coordinates | 7 |
world datasets | 7 |
primary seed | 7 |
statistical computing | 7 |
synthetic datasets | 7 |
distinct cell | 7 |
significant gwas | 7 |
com elakatos | 7 |
last month | 7 |
eas population | 7 |
hla associated | 7 |
protein data | 7 |
different lengths | 7 |
different similarity | 7 |
entry routes | 7 |
negative binomial | 7 |
module identification | 7 |
benchmark analysis | 7 |
tabu search | 7 |
lower values | 7 |
endothelial cells | 7 |
mononucleotide composition | 7 |
experimental em | 7 |
computational tool | 7 |
ub cl | 7 |
genes across | 7 |
data across | 7 |
engineered mouse | 7 |
sequencing technology | 7 |
pep slc | 7 |
ne le | 7 |
cancer subtypes | 7 |
xjeg http | 7 |
segment cns | 7 |
raw fastq | 7 |
protein levels | 7 |
internalisation degradation | 7 |
dashed lines | 7 |
sequences using | 7 |
activation function | 7 |
learning methods | 7 |
significantly lower | 6 |
zzqk nhfw | 6 |
phylogenetic orders | 6 |
fractal dimension | 6 |
gov pmc | 6 |
cd monocytes | 6 |
pangenome graph | 6 |
dna barcoding | 6 |
gender prop | 6 |
spike interaction | 6 |
combat correction | 6 |
gsea reactome | 6 |
es se | 6 |
row names | 6 |
supervised pca | 6 |
sequencing errors | 6 |
rna pol | 6 |
acting elements | 6 |
editing activity | 6 |
mass action | 6 |
cell level | 6 |
command takes | 6 |
score higher | 6 |
batch corrected | 6 |
simulated em | 6 |
highest ccn | 6 |
dna mutation | 6 |
protein fragment | 6 |
mg tablet | 6 |
ctd qaf | 6 |
fastq data | 6 |
will allow | 6 |
dna deletions | 6 |
sun exposure | 6 |
percentage points | 6 |
study design | 6 |
differential gene | 6 |
iff er | 6 |
another type | 6 |
repeat peaks | 6 |
gwas central | 6 |
bl vs | 6 |
cancer therapy | 6 |
reactome pathway | 6 |
interaction non | 6 |
iwwe http | 6 |
compute scalar | 6 |
expression combination | 6 |
bat coronavirus | 6 |
kax http | 6 |
wise scaling | 6 |
mer dosage | 6 |
receptor binding | 6 |
pa http | 6 |
parent ngsc | 6 |
around breakpoints | 6 |
convolutional networks | 6 |
la te | 6 |
ctd pgh | 6 |
johnson syndrome | 6 |
ifm http | 6 |
bps associated | 6 |
viterbi path | 6 |
cell births | 6 |
based algorithm | 6 |
lm http | 6 |
smrt rienrich | 6 |
multiplicative beta | 6 |
ctd gwpe | 6 |
short tandem | 6 |
number values | 6 |
gastrulation dataset | 6 |
obtained using | 6 |
additional clinical | 6 |
cell microscopy | 6 |
mouse tissue | 6 |
crispr cas | 6 |
binomial distribution | 6 |
additional details | 6 |
phirbo also | 6 |
base pairing | 6 |
ri ty | 6 |
prescription prodcodes | 6 |
datasets used | 6 |
core team | 6 |
mouse tissues | 6 |
cumulative distribution | 6 |
similarity metric | 6 |
immune cells | 6 |
inf model | 6 |
comparative analysis | 6 |
gender ami | 6 |
di pbmc | 6 |
fluorescence intensity | 6 |
confidence intervals | 6 |
adaptive learning | 6 |
trait composition | 6 |
ctd cq | 6 |
json file | 6 |
gbp gbp | 6 |
scrnaseq data | 6 |
genomes sampled | 6 |
convolutional noise | 6 |
euclidean pearson | 6 |
majority vote | 6 |
sequence space | 6 |
sequence reads | 6 |
normalized using | 6 |
high cross | 6 |
brain spatial | 6 |
intron length | 6 |
nt ia | 6 |
escherichia coli | 6 |
mrc cells | 6 |
weighted mean | 6 |
contact residues | 6 |
rpe gp | 6 |
oslo af | 6 |
variable importance | 6 |
high correlation | 6 |
bnwyax fojka | 6 |
species diversity | 6 |
ctd iybxb | 6 |
testtherapydf prodcode | 6 |
densely connected | 6 |
refseq database | 6 |
will also | 6 |
mm ammonium | 6 |
analysis showed | 6 |
permutation test | 6 |
lines screened | 6 |
receptor chain | 6 |
woi http | 6 |
subclonal proportion | 6 |
patients type | 6 |
described previously | 6 |
medical history | 6 |
ngsc di | 6 |
therapy data | 6 |
virome dataset | 6 |
either side | 6 |
function module | 6 |
abiotic connection | 6 |
mutational analysis | 6 |
bayes factor | 6 |
weight matrix | 6 |
highly enriched | 6 |
research council | 6 |
target sequences | 6 |
plos comput | 6 |
measured ms | 6 |
empirical distribution | 6 |
illumina infinium | 6 |
irf sirna | 6 |
fic ie | 6 |
population data | 6 |
reported scalar | 6 |
zzqk ifm | 6 |
cis containing | 6 |
negative association | 6 |
bayes factors | 6 |
latex kmc | 6 |
nda junctions | 6 |
fully connected | 6 |
polymerase chain | 6 |
wide profiling | 6 |
pancreatic cancer | 6 |
censor length | 6 |
melissa gymrek | 6 |
str http | 6 |
motifs show | 6 |
dominant subgroup | 6 |
chemotherapy response | 6 |
powell et | 6 |
meu http | 6 |
highly variable | 6 |
state annotations | 6 |
reading frames | 6 |
type composition | 6 |
plasminogen activator | 6 |
markov models | 6 |
ef fic | 6 |
sequence quality | 6 |
somatic copy | 6 |
tested whether | 6 |
qisc http | 6 |
data manifolds | 6 |
hypothetical goal | 6 |
sequencing run | 6 |
surface proteins | 6 |
la tio | 6 |
assessed using | 6 |
spearman correlation | 6 |
window parameter | 6 |
type annotation | 6 |
ace interaction | 6 |
highly accurate | 6 |
mg tablets | 6 |
two series | 6 |
cnuge debar | 6 |
patid unlist | 6 |
nucleotide sequence | 6 |
manual curation | 6 |
first drug | 6 |
com science | 6 |
true indel | 6 |
sulfone compounds | 6 |
independent validation | 6 |
se nt | 6 |
variants associated | 6 |
also called | 6 |
known donor | 6 |
protein interaction | 6 |
number tandem | 6 |
lived species | 6 |
methods sections | 6 |
co ef | 6 |
genome using | 6 |
viral entry | 6 |
models built | 6 |
grch hg | 6 |
pep htr | 6 |
cell syst | 6 |
composite score | 6 |
seq samples | 6 |
true scalar | 6 |
splicing patterns | 6 |
polar subgroups | 6 |
ifit ifit | 6 |
disease module | 6 |
zhou et | 6 |
formula difference | 6 |
different methods | 6 |
higher accuracy | 6 |
euclidean distances | 6 |
immune cell | 6 |
coi sequences | 6 |
seq profiles | 6 |
article pii | 6 |
healthy individuals | 6 |
influenza viruses | 6 |
local neighborhoods | 6 |
ms fragmentation | 6 |
sanger dataset | 6 |
gu la | 6 |
structural variation | 6 |
multivariable linear | 6 |
tracking data | 6 |
genomic regions | 6 |
position ref | 6 |
module detection | 6 |
biomedical imaging | 6 |
microscopy data | 6 |
life sciences | 6 |
cancer peaks | 6 |
hypothalamus data | 6 |
seven similarity | 6 |
njch http | 6 |
across diverse | 6 |
respiratory distress | 6 |
query samples | 6 |
numeric embryos | 6 |
known essential | 6 |
stem cell | 6 |
snp figure | 6 |
cell membrane | 6 |
viruses infecting | 6 |
one representative | 6 |
relative incompatibility | 6 |
ctd xd | 6 |
prokaryotic species | 6 |
ion peaks | 6 |
assess whether | 6 |
also tested | 6 |
ctd qanj | 6 |
region bias | 6 |
methylation data | 6 |
raw counts | 6 |
source software | 6 |
triplex dna | 6 |
multiple sequence | 6 |
silac media | 6 |
cytokine stimulation | 6 |
omics data | 6 |
cell transcriptomic | 6 |
individual cell | 6 |
effective length | 6 |
network structure | 6 |
size filtering | 6 |
calu cells | 6 |
summary statistics | 6 |
ng ml | 6 |
jqzsb http | 6 |
large scale | 6 |
consecutive genes | 6 |
reference rna | 6 |
least squares | 6 |
previously shown | 6 |
short reads | 6 |
re la | 6 |
mrna processing | 6 |
cancer subtype | 6 |
small membrane | 6 |
shared total | 6 |
kras mutation | 6 |
gyl http | 6 |
bnwyax rxwn | 6 |
exact test | 6 |
omic module | 6 |
uwiz http | 6 |
molecular features | 6 |
xgboost approach | 6 |
rsubread annotations | 6 |
er en | 6 |
standard errors | 6 |
may lead | 6 |
unphosphorylated stat | 6 |
control samples | 6 |
flagged sequences | 6 |
nsp nsp | 6 |
learning framework | 6 |
data manifold | 6 |
nucleotides surrounding | 6 |
fuzzy matching | 6 |
wildtype shown | 6 |
cardiac mechanics | 6 |
gut microbiome | 6 |
default splice | 6 |
cell associations | 6 |
indicate significance | 6 |
read alignment | 6 |
data types | 6 |
national cancer | 6 |
curvature estimate | 6 |
ctd wqpb | 6 |
measured cn | 6 |
detecting multiplets | 6 |
nervous system | 6 |
fixed neighborhood | 6 |
ranking lists | 6 |
normal cells | 6 |
tumor rna | 6 |
penalty parameter | 6 |
reasonably distanced | 6 |
reference genomes | 6 |
nearest neighbour | 6 |
recent refseq | 6 |
elegans embryo | 6 |
step bleaching | 6 |
zwnw http | 6 |
wise majority | 6 |
experimental results | 6 |
pstat kinetics | 6 |
based indices | 6 |
closest points | 6 |
mappability analysis | 6 |
adverse drug | 6 |
ctd jqzsb | 6 |
alignment file | 6 |
locus length | 6 |
chromatin states | 6 |
im ila | 6 |
community diversity | 6 |
relevant gene | 6 |
prokaryotic sequences | 6 |
analysis using | 6 |
genomic profiles | 6 |
international journal | 6 |
igv snapshot | 6 |
idt af | 6 |
bnwyax votga | 6 |
per nuclei | 6 |
variants identified | 6 |
novel virus | 6 |
used candi | 6 |
gene expressions | 6 |
cytoplasmic phosphorylated | 6 |
taxonomic levels | 6 |
investigated whether | 6 |
novel species | 6 |
available via | 6 |
dependency profiles | 6 |
mrna targets | 6 |
selective dependencies | 6 |
quality genomes | 6 |
labelled cancer | 6 |
ctd cclhp | 6 |
eqtl mapping | 6 |
tablet oral | 6 |
learn cell | 6 |
go similarity | 6 |
also provide | 6 |
ie nt | 6 |
zzqk njch | 6 |
purity estimation | 6 |
sabaeus vero | 6 |
sequences flagged | 6 |
diseases like | 6 |
annotation contains | 6 |
nearest neighbor | 6 |
ncbi annotations | 6 |
strain values | 6 |
rxwn http | 6 |
genomic analysis | 6 |
sirna irf | 6 |
well suited | 6 |
rna splicing | 6 |
levels induced | 6 |
classification profile | 6 |
data based | 6 |
average precision | 6 |
total il | 6 |
existing methods | 6 |
splice variants | 6 |
stat levels | 6 |
seed nodes | 6 |
ef fe | 6 |
sample variation | 6 |
root ganglion | 6 |
gbp stat | 6 |
lecif score | 6 |
ld http | 6 |
line treatment | 6 |
end reads | 6 |
phylogenetic tree | 6 |
ctd lyx | 6 |
dorsal root | 6 |
consistently high | 6 |
allele matching | 6 |
cas targeting | 6 |
human islet | 6 |
random forests | 6 |
without bias | 6 |
chem inf | 6 |
contingency table | 6 |
significant module | 6 |
relative contribution | 6 |
spacer length | 6 |
correlation analysis | 6 |
bars indicate | 6 |
final output | 6 |
solid red | 6 |
schematic representation | 6 |
toy manifolds | 6 |
sigma sigma | 6 |
canberra index | 6 |
tissue labels | 6 |
intramolecular triplex | 6 |
unchanged regulated | 6 |
receptor complexes | 6 |
two distinct | 6 |
repeated times | 6 |
jak stat | 6 |
liver cancer | 6 |
loop structure | 6 |
values correspond | 6 |
difference image | 6 |
representative experiment | 6 |
experimental techniques | 6 |
re interaction | 6 |
bp long | 6 |
biomedical research | 6 |
results show | 6 |
rm al | 6 |
com cnuge | 6 |
better performance | 6 |
liver extract | 6 |
gtf file | 6 |
ila ri | 6 |
known cell | 6 |
broad range | 6 |
aligned reads | 6 |
nucleotide sequences | 6 |
analysis shows | 6 |
ovarian carcinoma | 6 |
canonical splicing | 6 |
ref https | 6 |
fenjn http | 6 |
statistical methods | 6 |
biological chemistry | 6 |
data structures | 6 |
vae encoding | 6 |
ms multi | 6 |
linear gradients | 6 |
multivariable model | 6 |
new potential | 6 |
fe ct | 6 |
du ct | 6 |
results demonstrate | 6 |
genomic concordance | 6 |
search tool | 6 |
hypothalamus mammary | 6 |
significantly larger | 6 |
forming motifs | 6 |
relatively low | 6 |
left side | 6 |
sashimi plot | 6 |
candidate annotation | 6 |
selected genes | 6 |
mock treated | 6 |
chain reaction | 6 |
science article | 6 |
complementation factor | 6 |
cell tracking | 6 |
counting dimension | 6 |
tumor data | 6 |
normalization method | 6 |
content eaat | 6 |
zzqk rjuf | 6 |
ctd hn | 6 |
braukmann et | 6 |
conditional genetic | 6 |
microarray genes | 6 |
umi counts | 5 |
virus reads | 5 |
huang et | 5 |
room temperature | 5 |
data mining | 5 |
full set | 5 |
order terms | 5 |
nonrepetitive regions | 5 |
durbin et | 5 |
sanger institutes | 5 |
testing dataset | 5 |
terwilliger tc | 5 |
binomial test | 5 |
determine whether | 5 |
cyclical fluctuations | 5 |
exonic bases | 5 |
given species | 5 |
functional relationships | 5 |
tumour cell | 5 |
receptor molecules | 5 |
genomic position | 5 |
genomics level | 5 |
also removed | 5 |
optimum expression | 5 |
transmitted light | 5 |
massively parallel | 5 |
likely due | 5 |
current scrnaseq | 5 |
derived metabolites | 5 |
deepmm achieved | 5 |
using combat | 5 |
predicted atu | 5 |
xl http | 5 |
clustering algorithms | 5 |
high positive | 5 |
beta values | 5 |
methylation profiles | 5 |
structure overlap | 5 |
existing iao | 5 |
east asian | 5 |
pacific symposium | 5 |
statistical power | 5 |
chat bs | 5 |
hg amr | 5 |
human orthologous | 5 |
average bf | 5 |
cells born | 5 |
human tissue | 5 |
simulated maps | 5 |
sfn http | 5 |
multiplet annotations | 5 |
also enriched | 5 |
subclonal scnas | 5 |
gene lists | 5 |
rpd http | 5 |
nominal tumor | 5 |
ieee transactions | 5 |
homologous sequences | 5 |
using single | 5 |
correction method | 5 |
average values | 5 |
en es | 5 |
gse dataset | 5 |
clinical decision | 5 |
dguv http | 5 |
stat identity | 5 |
two species | 5 |
kegg pathway | 5 |
functional ecology | 5 |
kl http | 5 |
th differentiation | 5 |
systemic lupus | 5 |
cell shape | 5 |
python package | 5 |
greater number | 5 |
relatively flat | 5 |
shared genes | 5 |
plots show | 5 |
island status | 5 |
lisinopril atenolol | 5 |
points reported | 5 |
pjd http | 5 |
pair transformation | 5 |
fractional methylation | 5 |
cell identity | 5 |
singular value | 5 |
four scrna | 5 |
dunn index | 5 |
motifs compared | 5 |
strain estimation | 5 |
candidate position | 5 |
specific error | 5 |
zzqk iq | 5 |
orthologous genes | 5 |
kendall tau | 5 |
reference panels | 5 |
ifz http | 5 |
rpd https | 5 |
overall accuracy | 5 |
biochemical connection | 5 |
methylation studies | 5 |
high performance | 5 |
host response | 5 |
frankfurt strain | 5 |
loop reference | 5 |
learning association | 5 |
series analysis | 5 |
norm score | 5 |
expression omnibus | 5 |
batch effect | 5 |
immunotherapy targets | 5 |
qaf http | 5 |
atom structure | 5 |
special characters | 5 |
see data | 5 |
ratio estimates | 5 |
classifier using | 5 |
ari scores | 5 |
mirror repeats | 5 |
cells per | 5 |
high throughput | 5 |
numeric labels | 5 |
positive rate | 5 |
com tianyu | 5 |
silhouette width | 5 |
legends figure | 5 |
large ambient | 5 |
train set | 5 |
seq gene | 5 |
mapped fragments | 5 |
tolerated mutations | 5 |
heatmap representation | 5 |
yulf http | 5 |
unstable segments | 5 |
molecular networking | 5 |
qanj http | 5 |
circumferential ess | 5 |
labeled tumor | 5 |
made use | 5 |
significance threshold | 5 |
editing efficiency | 5 |
significance level | 5 |
simulated spatial | 5 |
next step | 5 |
allow us | 5 |
smith hc | 5 |
complex stabilization | 5 |
ctd oc | 5 |
target genes | 5 |
trabecular meshwork | 5 |
parameter tuning | 5 |
four samples | 5 |
high scores | 5 |
bonferroni correction | 5 |
learning cell | 5 |
residues fav | 5 |
done using | 5 |
string database | 5 |
left panel | 5 |