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Judith Somekh

Researcher at University of Haifa

Publications -  18
Citations -  339

Judith Somekh is an academic researcher from University of Haifa. The author has contributed to research in topics: Conceptual model & Modeling language. The author has an hindex of 6, co-authored 15 publications receiving 194 citations. Previous affiliations of Judith Somekh include Harvard University & Technion – Israel Institute of Technology.

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Ulcerative colitis mucosal transcriptomes reveal mitochondriopathy and personalized mechanisms underlying disease severity and treatment response

TL;DR: In this article, the authors used RNAseq to define pre-treatment rectal gene expression, and fecal microbiota profiles, in 206 pediatric ulcerative colitis patients receiving standardised therapy.

Ulcerative colitis mucosal transcriptomes reveal mitochondriopathy and personalized mechanisms underlying disease severity and treatment response

TL;DR: Examination of rectal gene expression signatures and faecal microbiomes of children and adults with ulcerative colitis provides insights into UC pathogenesis, and may prioritise future therapies for nonresponders to current approaches.
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A methodology for eliciting and modeling exceptions

TL;DR: A conceptual model of exceptions, a methodology for eliciting and modeling exceptions, and templates for modeling them in an extension of the Object-Process Methodology-a system analysis and design methodology and language that uses a single graphical model for describing systems, including their timing exceptions, which has been shown to be an effective modeling methodology.
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Conceptual Modeling of mRNA Decay Provokes New Hypotheses

TL;DR: Using Object-Process Methodology (OPM), a formal yet visual and humanly accessible conceptual modeling language, an executable working model of the mRNA decay process in Saccharomyces cerevisiae is created, as well as the import of its components to the nucleus following mRNA decay.
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Batch correction evaluation framework using a-priori gene-gene associations: applied to the GTEx dataset

TL;DR: A novel framework, B-CeF, is described to evaluate the effectiveness of batch correction methods and their tendency toward over or under correction and shows that using a multiple linear regression model to correct for known confounder outperforms factor analysis-based methods that estimate hidden confounders.