Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data.
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A gene regulatory network for root epidermis cell differentiation in ArabidopsisPartially observed bipartite network analysis to identify predictive connections in transcriptional regulatory networksEffective connectivity analysis of fMRI and MEG data collected under identical paradigms.RegNetB: predicting relevant regulator-gene relationships in localized prostate tumor samples.Systems biology data analysis methodology in pharmacogenomics.
P2860
Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data.
description
2009 nî lūn-bûn
@nan
2009 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
name
Python Environment for Bayesia ...... works from Knowledge and Data.
@ast
Python Environment for Bayesia ...... works from Knowledge and Data.
@en
Python Environment for Bayesia ...... works from Knowledge and Data.
@nl
type
label
Python Environment for Bayesia ...... works from Knowledge and Data.
@ast
Python Environment for Bayesia ...... works from Knowledge and Data.
@en
Python Environment for Bayesia ...... works from Knowledge and Data.
@nl
prefLabel
Python Environment for Bayesia ...... works from Knowledge and Data.
@ast
Python Environment for Bayesia ...... works from Knowledge and Data.
@en
Python Environment for Bayesia ...... works from Knowledge and Data.
@nl
P2860
P1476
Python Environment for Bayesia ...... tworks from Knowledge and Data
@en
P2093
Abhik Shah
Peter Woolf
P2860
P304
P407
P577
2009-06-01T00:00:00Z