Prediction of oncogenic interactions and cancer-related signaling networks based on network topology.
about
Multi-label multi-instance transfer learning for simultaneous reconstruction and cross-talk modeling of multiple human signaling pathwaysLarge-scale integration of small molecule-induced genome-wide transcriptional responses, Kinome-wide binding affinities and cell-growth inhibition profiles reveal global trends characterizing systems-level drug action.Hierarchical closeness-based properties reveal cancer survivability and biomarker genes in molecular signaling networks.
P2860
Prediction of oncogenic interactions and cancer-related signaling networks based on network topology.
description
2013 nî lūn-bûn
@nan
2013 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
name
Prediction of oncogenic intera ...... rks based on network topology.
@ast
Prediction of oncogenic intera ...... rks based on network topology.
@en
type
label
Prediction of oncogenic intera ...... rks based on network topology.
@ast
Prediction of oncogenic intera ...... rks based on network topology.
@en
prefLabel
Prediction of oncogenic intera ...... rks based on network topology.
@ast
Prediction of oncogenic intera ...... rks based on network topology.
@en
P2860
P1433
P1476
Prediction of oncogenic intera ...... orks based on network topology
@en
P2093
Esther Camilo
P2860
P304
P356
10.1371/JOURNAL.PONE.0077521
P407
P577
2013-10-25T00:00:00Z