id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-327651-yzwsqlb2	Ray, Bisakha	Network inference from multimodal data: A review of approaches from infectious disease transmission	2016-09-06		.txt	text/plain	7198	353	33	In infectious disease transmission network inference, Bayesian inference frameworks have been primarily used to integrate data such as dates of pathogen sample collection and symptom report date, pathogen genome sequences, and locations of patients [24] [25] [26] . Pathogen genomic data can capture within-host pathogen diversity (the product of effective population size in a generation and the average pathogen replication time [25, 26] ) and dynamics or provide information critical to understanding disease transmission such as evidence of new transmission pathways that cannot be inferred from epidemiological data alone [40, 41] . As molecular epidemiology and infectious disease transmission are areas in which network inference methods have been developed for bringing together multimodal data we use this review to investigate the foundational work in this specific field. In this section we briefly review multimodal integration methods for combining pathogen genomic data and epidemiological data in a single analysis, for inferring infection transmission trees and epidemic dynamic parameters.	./cache/cord-327651-yzwsqlb2.txt	./txt/cord-327651-yzwsqlb2.txt