Literature DB >> 30717676

A new version of the ANDSystem tool for automatic extraction of knowledge from scientific publications with expanded functionality for reconstruction of associative gene networks by considering tissue-specific gene expression.

Vladimir A Ivanisenko1,2, Pavel S Demenkov3,4, Timofey V Ivanisenko3,4, Elena L Mishchenko3, Olga V Saik3,4.   

Abstract

BACKGROUND: Consideration of tissue-specific gene expression in reconstruction and analysis of molecular genetic networks is necessary for a proper description of the processes occurring in a specified tissue. Currently, there are a number of computer systems that allow the user to reconstruct molecular-genetic networks using the data automatically extracted from the texts of scientific publications. Examples of such systems are STRING, Pathway Commons, MetaCore and Ingenuity. The MetaCore and Ingenuity systems permit taking into account tissue-specific gene expression during the reconstruction of gene networks. Previously, we developed the ANDSystem tool, which also provides an automated extraction of knowledge from scientific texts and allows the reconstruction of gene networks. The main difference between our system and other tools is in the different types of interactions between objects, which makes the ANDSystem complementary to existing well-known systems. However, previous versions of the ANDSystem did not contain any information on tissue-specific expression.
RESULTS: A new version of the ANDSystem has been developed. It offers the reconstruction of associative gene networks while taking into account the tissue-specific gene expression. The ANDSystem knowledge base features information on tissue-specific expression for 272 tissues. The system allows the reconstruction of combined gene networks, as well as performing the filtering of genes from such networks using the information on their tissue-specific expression. As an example of the application of such filtering, the gene network of the extrinsic apoptotic signaling pathway was analyzed. It was shown that considering different tissues can lead to changes in gene network structure, including changes in such indicators as betweenness centrality of vertices, clustering coefficient, network centralization, network density, etc.
CONCLUSIONS: The consideration of tissue specificity can play an important role in the analysis of gene networks, in particular solving the problem of finding the most significant central genes. Thus, the new version of ANDSystem can be employed for a wide range of tasks related to biomedical studies of individual tissues. It is available at http://www-bionet.sscc.ru/and/cell /.

Entities:  

Keywords:  ANDSystem; Associative gene networks; Automated extraction of knowledge; Extrinsic apoptotic signaling pathway; Text-mining; Tissue-specific gene expression

Mesh:

Year:  2019        PMID: 30717676      PMCID: PMC6362586          DOI: 10.1186/s12859-018-2567-6

Source DB:  PubMed          Journal:  BMC Bioinformatics        ISSN: 1471-2105            Impact factor:   3.169


  42 in total

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Review 3.  Apoptosis and caspases in neurodegenerative diseases.

Authors:  Robert M Friedlander
Journal:  N Engl J Med       Date:  2003-04-03       Impact factor: 91.245

Review 4.  Computational systems biology.

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Authors:  P M Eimon; E Kratz; E Varfolomeev; S G Hymowitz; H Stern; J Zha; A Ashkenazi
Journal:  Cell Death Differ       Date:  2006-08-04       Impact factor: 15.828

Review 7.  Apoptosis in autoimmune diseases.

Authors:  K Eguchi
Journal:  Intern Med       Date:  2001-04       Impact factor: 1.271

Review 8.  Tissue specificity of apoptotic signal transduction.

Authors:  Yoshinori Otsuki
Journal:  Med Electron Microsc       Date:  2004-09

Review 9.  Death receptor-induced cell killing.

Authors:  Andrew Thorburn
Journal:  Cell Signal       Date:  2004-02       Impact factor: 4.315

10.  Understanding network concepts in modules.

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6.  A Catalog of Human Genes Associated With Pathozoospermia and Functional Characteristics of These Genes.

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Journal:  Front Genet       Date:  2021-07-05       Impact factor: 4.599

7.  Bioinformatic Reconstruction and Analysis of Gene Networks Related to Glucose Variability in Diabetes and Its Complications.

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