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Molecular Networks in Mammals: Extraction from Literature and Pathway Analysis
Ariadne Genomics, Inc.
Using the proprietary high-content linguistics tool MedScan we compiled a comprehensive
database of molecular networks by extracting the information from scientific literature.
MedScan is capable of extracting functional associations between proteins, small molecules,
and pathways, recognizes types of regulatory mechanisms involved, effects of regulation and
experimental conditions.
The resulting database stores 700,000 relationships between mammalian proteins and
chemicals including facts about protein interactions, promoter binding, molecular
biosynthesis and trafficking, and cell process regulation. Different approaches towards
reconstructing individual pathways or cascades from this database and assigning functional
categories to proteins will be described.
Our visualization software is capable of systematically mining this database for small network
motifs that are robust in regard to the effects induced at the gene expression levels. We have
also developed a Bayesian framework for integration of microarray data and binary gene-togene
regulatory relationships. The approach allows the reduction of expression pattern
complexity and finds the minimal set of regulatory proteins that are responsible for
differential expression of other genes.
Finding mesoscopic communities in sparse networks
I. Ispolatov, I. Mazo, and A. Yuryev
q-bio.MN/0512038, submitted to Phys. Rev. E
Identifying Local Gene Expression Patterns in Biomolecular Networks
A. Y. Sivachenko, A. Yuryev, N. Daraselia, I. Mazo
2005 IEEE Computational Systems Bioinformatics Conference, Aug. 8-11, 2005
Cliques and duplication-divergence network growth
Ispolatov, I ; Krapivsky, P L ; Mazo, I ; Yuryev, A
New J.Phys. 7(2005) 145
Binding properties and evolution of homodimers in protein-protein interaction networks
Ispolatov, Iaroslav; Yuryev, Anton; Mazo, Ilya; Maslov, Sergei
Nucleic Acids Research 2005 33(11):3629-3635
Extracting Protein Function Information from MEDLINE Using a Full-Sentence Parser
Nikolai Daraselia, Sergei Egorov, Andrey Yazhuk, Svetlana Novichkova, Anton Yuryev, Ilya Mazo
published in Proceeding of the Second European Workshop on Data Mining and Text Mining for
Bioinformatics, pp11-18, 2004
A Simple and Practical Dictionary-Based Approach for Identification of Proteins in MEDLINE Abstracts
Sergei Egorov PhD, Anton Yuryev PhD, and Nikolai Daraselia PhD
Journal of the American Medical Informatics Association 2004
Pathway studio - the analysis and navigation of molecular networks
Alexander Nikitin, Sergei Egorov, Nikolai Daraselia and Ilya Mazo
BIOINFORMATICS APPLICATIONS NOTE Vol. 19 no. 0 2003, pages 1-3
Extracting human protein interactions from MEDLINE using a full-sentence parser
Nikolai Daraselia, Anton Yuryev, Sergei Egorov, Svetalana Novichkova, Alexander Nikitin and Ilya Mazo
BIOINFORMATICS Vol. 19 no. 0 2003, pages 1–8
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