Ideker Lab - UC San Diego
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1 News 161 Publications 32 Members

Coevolution within a transcriptional network by compensatory trans and cis mutations.

Kuo, D Kate Licon Bandyopadhyay, S Chuang, R Luo, C Catalana, J Ravasi, T Tan, K Trey Ideker

Published in Genome Research

Transcriptional networks have been shown to evolve very rapidly, prompting questions as to how such changes arise and are tolerated. Recent comparisons of transcriptional networks across species have implicated variations in the cis-acting DNA sequences near genes as the main cause of divergence. What is less clear is how these changes interact wit...

Multiple pathways are co-regulated by the protein kinase Snf1 and the transcription factors Adr1 and Cat8.

Young, Et Dombek, Km Tachibana, C Trey Ideker

Published in Journal of Biological Chemistry

ADR1 and CAT8 encode carbon source-responsive transcriptional regulators that cooperatively control expression of genes involved in ethanol utilization. These transcription factors are active only after the diauxic transition, when glucose is depleted and energy-generating metabolism has shifted to the aerobic oxidation of non-fermentable carbon so...

Mining SNPs from EST databases.

Picoult-Newberg, L Trey Ideker Pohl, Mg Taylor, Sl Donaldson, Ma Nickerson, Da Boyce-Jacino, M

Published in Genome Research

There is considerable interest in the discovery and characterization of single nucleotide polymorphisms (SNPs) to enable the analysis of the potential relationships between human genotype and phenotype. Here we present a strategy that permits the rapid discovery of SNPs from publicly available expressed sequence tag (EST) databases. From a set of E...

Integrating scientific cultures.

Trey Ideker Bafna, V Lemberger, T

Published in Molecular Systems Biology

Physical network models.

Yeang, Ch Trey Ideker Jaakkola, T

Published in Journal of Computational Biology

We develop a new framework for inferring models of transcriptional regulation. The models, which we call physical network models, are annotated molecular interaction graphs. The attributes in the model correspond to verifiable properties of the underlying biological system such as the existence of protein-protein and protein-DNA interactions, the d...

A direct comparison of protein interaction confidence assignment schemes.

Suthram, S Shlomi, T Ruppin, E Sharan, R Trey Ideker

Published in BMC Bioinformatics

CellCircuits: a database of protein network models.

Mak, Hc Daly, M Gruebel, B Trey Ideker

Published in Nucleic Acids Research

CellCircuits (http://www.cellcircuits.org) is an open-access database of molecular network models, designed to bridge the gap between databases of individual pairwise molecular interactions and databases of validated pathways. CellCircuits captures the output from an increasing number of approaches that screen molecular interaction networks to iden...

Improving breast cancer survival analysis through competition-based multidimensional modeling.

Bilal, E Dutkowski, J Guinney, J Jang, Is Logsdon, Ba Pandey, G Sauerwine, Ba Shimoni, Y Moen Vollan, Hk Mecham, Bh ...

Published in PLoS Computational Biology

Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one aven...

Yeast PP4 interacts with ATR homolog Ddc2-Mec1 and regulates checkpoint signaling.

Hustedt, N Seeber, A Sack, R Tsai-Pflugfelder, M Bhullar, B Vlaming, H Van Leeuwen, F Guénolé, A Van Attikum, H Srivas, R ...

Published in Molecular Cell

Mec1-Ddc2 (ATR-ATRIP) controls the DNA damage checkpoint and shows differential cell-cycle regulation in yeast. To find regulators of Mec1-Ddc2, we exploited a mec1 mutant that retains catalytic activity in G2 and recruitment to stalled replication forks, but which is compromised for the intra-S phase checkpoint. Two screens, one for spontaneous su...

An atlas of combinatorial transcriptional regulation in mouse and man.

Ravasi, T Suzuki, H Cannistraci, Cv Katayama, S Bajic, Vb Tan, K Akalin, A Schmeier, S Kanamori-Katayama, M Bertin, N ...

Published in Cell

Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions....

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