Literature DB >> 16448026

Multi-knockout genetic network analysis: the Rad6 example.

Alon Kaufman1, Martin Kupiec, Eytan Ruppin.   

Abstract

A novel and rigorous Multi-perturbation Shapley Value Analysis (MSA) method has been recently presented [12]. The method addresses the challenge of defining and calculating the functional causal contributions of elements of a biological system. This paper presents the first study applying MSA to the analysis of gene knockout data. The MSA identifies the importance of genes in the Rad6 DNA repair pathway of the yeast S. cerevisiae, quantifying their contributions and characterizing their functional interactions. Incorporating additional biological knowledge, a new functional description of the Rad6 pathway is provided, predicting the existence of additional DNA polymerase and RFC-like complexes. The MSA is the first method for rigorously analyzing multi-knockout experiments, which are likely to soon become a standard and necessary tool for analyzing complex biological systems.

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Year:  2004        PMID: 16448026

Source DB:  PubMed          Journal:  Proc IEEE Comput Syst Bioinform Conf        ISSN: 1551-7497


  4 in total

1.  Multiperturbation analysis of distributed neural networks: the case of spatial neglect.

Authors:  Alon Kaufman; Corinne Serfaty; Leon Y Deouell; Eytan Ruppin; Nachum Soroker
Journal:  Hum Brain Mapp       Date:  2009-11       Impact factor: 5.038

2.  Exploring the limitations of biophysical propensity scales coupled with machine learning for protein sequence analysis.

Authors:  Daniele Raimondi; Gabriele Orlando; Wim F Vranken; Yves Moreau
Journal:  Sci Rep       Date:  2019-11-15       Impact factor: 4.379

3.  Technical considerations of a game-theoretical approach for lesion symptom mapping.

Authors:  Melissa Zavaglia; Nils D Forkert; Bastian Cheng; Christian Gerloff; Götz Thomalla; Claus C Hilgetag
Journal:  BMC Neurosci       Date:  2016-06-27       Impact factor: 3.288

4.  Ambiguity in logic-based models of gene regulatory networks: An integrative multi-perturbation analysis.

Authors:  Amir Reza Alizad-Rahvar; Mehdi Sadeghi
Journal:  PLoS One       Date:  2018-11-20       Impact factor: 3.240

  4 in total

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