De-novo learning of genome-scale regulatory networks in S. cerevisiae.
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An Evaluation of Active Learning Causal Discovery Methods for Reverse-Engineering Local Causal Pathways of Gene RegulationExploring candidate biological functions by Boolean Function Networks for Saccharomyces cerevisiae.Condition-Specific Modeling of Biophysical Parameters Advances Inference of Regulatory Networks.IncGraph: Incremental graphlet counting for topology optimisation.A comprehensive evaluation of module detection methods for gene expression data.In Silico Prediction of Large-Scale Microbial Production Performance: Constraints for Getting Proper Data-Driven Models
P2860
De-novo learning of genome-scale regulatory networks in S. cerevisiae.
description
2014 nî lūn-bûn
@nan
2014 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
De-novo learning of genome-scale regulatory networks in S. cerevisiae.
@ast
De-novo learning of genome-scale regulatory networks in S. cerevisiae.
@en
type
label
De-novo learning of genome-scale regulatory networks in S. cerevisiae.
@ast
De-novo learning of genome-scale regulatory networks in S. cerevisiae.
@en
prefLabel
De-novo learning of genome-scale regulatory networks in S. cerevisiae.
@ast
De-novo learning of genome-scale regulatory networks in S. cerevisiae.
@en
P2093
P2860
P1433
P1476
De-novo learning of genome-scale regulatory networks in S. cerevisiae
@en
P2093
Alexander Statnikov
David Gresham
P2860
P304
P356
10.1371/JOURNAL.PONE.0106479
P407
P577
2014-09-12T00:00:00Z