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Jill P. Mesirov
University of California, San Diego
227Publications
71H-index
104kCitations
Publications 227
Newest
Published on Apr 23, 2019in Neuro-oncology 9.38
Konstantin Okonechnikov3
Estimated H-index: 3
(German Cancer Research Center),
Jens-Martin Hübner1
Estimated H-index: 1
(German Cancer Research Center)
+ 10 AuthorsJesse R. Dixon15
Estimated H-index: 15
(Salk Institute for Biological Studies)
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Published on Mar 1, 2019in Molecular & Cellular Proteomics 5.24
Karsten Krug14
Estimated H-index: 14
,
Philipp Mertins27
Estimated H-index: 27
+ 14 AuthorsJudit Jané-Valbuena9
Estimated H-index: 9
Signaling pathways are orchestrated by post-translational modifications (PTMs) such as phosphorylation. However, pathway analysis of PTM datasets generated by mass spectrometry (MS)-based proteomics is typically performed at a gene-centric level due to the lack of appropriately curated PTM signature databases and bioinformatic tools that leverage PTM site-specific information. Here we present the first version of PTMsigDB, a database of modification site-specific signatures of perturbations, kin...
2 Citations Source Cite
Published on Dec 5, 2018in F1000Research
Clarence K. Mah2
Estimated H-index: 2
(University of California, San Diego),
Jill P. Mesirov71
Estimated H-index: 71
(University of California, San Diego),
Lukas Chavez25
Estimated H-index: 25
(University of California, San Diego)
Illumina Infinium DNA methylation arrays are a cost-effective technology to measure DNA methylation at CpG sites genome-wide and across cohorts of normal and cancer samples. While copy number alterations are commonly inferred from array-CGH, SNP arrays, or whole-genome DNA sequencing, Illumina Infinium DNA methylation arrays have been shown to detect copy number alterations at comparable sensitivity. Here we present an accessible, interactive GenePattern notebook for the analysis of copy number ...
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Published on Nov 1, 2018
Steven E. Brenner55
Estimated H-index: 55
(University of California, Berkeley),
Martha L. Bulyk48
Estimated H-index: 48
(Brigham and Women's Hospital)
+ 3 AuthorsPredrag Radivojac41
Estimated H-index: 41
(Indiana University)
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Published on Oct 12, 2018in F1000Research
Daniel E. Carlin11
Estimated H-index: 11
(University of California, San Diego),
Forrest Kim (University of California, San Diego)+ 1 AuthorsJill P. Mesirov71
Estimated H-index: 71
(University of California, San Diego)
We present a unified GenomeSpace recipe that combines the results of a high throughput CRISPR genetic screen and a biological network to return a subnetwork that suggests a mechanistic explanation of the screen’s results. The explanatory subnetwork is found by network propagation, a popular systems biology approach. We demonstrate our pipeline on an alpha toxin screen, revealing a subnetwork that is both highly interconnected and highly enriched for hits in the screen.
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Published on Sep 1, 2018in Cancer Cell 22.84
Tenley C. Archer11
Estimated H-index: 11
,
Tobias Ehrenberger8
Estimated H-index: 8
(Massachusetts Institute of Technology)
+ 28 AuthorsDivya Ramamoorthy2
Estimated H-index: 2
(Massachusetts Institute of Technology)
Summary There is a pressing need to identify therapeutic targets in tumors with low mutation rates such as the malignant pediatric brain tumor medulloblastoma. To address this challenge, we quantitatively profiled global proteomes and phospho-proteomes of 45 medulloblastoma samples. Integrated analyses revealed that tumors with similar RNA expression vary extensively at the post-transcriptional and post-translational levels. We identified distinct pathways associated with two subsets of SHH tumo...
10 Citations Source Cite
Published on Aug 16, 2018in F1000Research
Clarence K. Mah2
Estimated H-index: 2
(University of California, San Diego),
Thorin Tabor2
Estimated H-index: 2
(University of California, San Diego),
Jill P. Mesirov71
Estimated H-index: 71
(University of California, San Diego)
Single-cell RNA sequencing (scRNA-seq) has emerged as a popular method to profile gene expression at the resolution of individual cells. While there have been methods and software specifically developed to analyze scRNA-seq data, they are most accessible to users who program. We have created a scRNA-seq clustering analysis GenePattern Notebook that provides an interactive, easy-to-use interface for data analysis and exploration of scRNA-Seq data, without the need to write or view any code. The n...
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Published on Jul 1, 2018
Michael M. Reich2
Estimated H-index: 2
,
Thorin Tabor2
Estimated H-index: 2
+ 3 AuthorsJill P. Mesirov71
Estimated H-index: 71
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Published on Jul 1, 2018in Nature Methods 26.92
Taibo Li2
Estimated H-index: 2
,
April Kim2
Estimated H-index: 2
(Broad Institute)
+ 22 AuthorsTed Natoli6
Estimated H-index: 6
(Broad Institute)
Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to compare the signal-to-noise ratios of different networks and to identify the optimal network with which to interpret a particular genetic dataset. We present GeNets, a platform in which users can train a machine-learning model (Quack) to carry out these comparisons and execute, store, and share analyses of genetic and RNA-sequencing datasets.
5 Citations Source Cite
Published on Jul 1, 2018in Cancer Research 9.13
Huwate Yeerna4
Estimated H-index: 4
(University of California, San Diego),
William Y. Kim42
Estimated H-index: 42
(Harvard University)
+ 2 AuthorsPablo Tamayo56
Estimated H-index: 56
(University of California, San Diego)
We used a skew-distribution-based statistical methodology to fit parametric models of cell-viability profiles from genome-wide RNAi-gene knockdowns. We identify the subset of genes with the highest degree of skewness that represent most oncogenes and tumor suppressors. We decomposed those genes using matrix decomposition in order to define mutual vulnerabilities. The resulting matrix decomposition components represent coordinated patterns of gene dependency shared by many genes in many cell line...
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