Literature DB >> 23811083

Computational studies on Alzheimer's disease associated pathways and regulatory patterns using microarray gene expression and network data: revealed association with aging and other diseases.

Priya P Panigrahi1, Tiratha Raj Singh.   

Abstract

Alzheimer's disease (AD), which is one of the most common age-associated neurodegenerative disorders, affects millions of people worldwide. Due to its polygenic nature, AD is believed to be caused not by defects in single genes, but by variations in a large number of genes and their complex interactions, which ultimately contribute to the broad spectrum of disease phenotypes. Extraction of insights and knowledge from microarray and network data will lead to a better understanding of complex diseases. The present study aimed to identify genes with differential topology and their further association with other biological processes that regulate causative factors for AD, ageing (AG) and other diseases. Our analysis revealed a common sharing of important biological processes and putative candidate genes among AD and AG. Some significant novel genes and other variants for various biological processes have been reported as being associated with AD, AG, and other diseases, and these could be implicated in biochemical events leading to AD from AG through pathways, interactions, and associations. Novel information for network motifs such as BiFan, MIM (multiple input module), and SIM (single input module) and their close variants has also been discovered and this implicit information will help to improve research into AD and AG. Ten major classes for TFs (transcription factors) have been identified in our data, where hundreds of TFBS patterns are being found associated with AD, and other disease. Structural and physico-chemical properties analysis for these TFBS classes revealed association of biological processes involved with other severe human disease. Nucleosomes and linkers positional information could provide insights into key cellular processes. Unique miRNA (micro RNA) targets were identified as another regulatory process for AD. The association of novel genes and variants of existing genes have also been explored for their interaction and association with other diseases that are either directly or indirectly implicated through AG and AD.
Copyright © 2013 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Enrichment analysis; Mirna; Network motifs; Nucleosomes; TFBS

Mesh:

Year:  2013        PMID: 23811083     DOI: 10.1016/j.jtbi.2013.06.013

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  7 in total

Review 1.  Exploring Biomarkers for Alzheimer's Disease.

Authors:  Neeti Sharma; Anshika Nikita Singh
Journal:  J Clin Diagn Res       Date:  2016-07-01

2.  Regional vulnerability in Alzheimer's disease: The role of cell-autonomous and transneuronal processes.

Authors:  Diana Acosta; Fontasha Powell; Yize Zhao; Ashish Raj
Journal:  Alzheimers Dement       Date:  2018-01-04       Impact factor: 21.566

3.  ABCD: Alzheimer's disease Biomarkers Comprehensive Database.

Authors:  Ashwani Kumar; Ankush Bansal; Tiratha Raj Singh
Journal:  3 Biotech       Date:  2019-09-03       Impact factor: 2.406

4.  Dynamic regulatory network reconstruction for Alzheimer's disease based on matrix decomposition techniques.

Authors:  Wei Kong; Xiaoyang Mou; Xing Zhi; Xin Zhang; Yang Yang
Journal:  Comput Math Methods Med       Date:  2014-06-15       Impact factor: 2.238

Review 5.  The Application of Artificial Intelligence in the Genetic Study of Alzheimer's Disease.

Authors:  Rohan Mishra; Bin Li
Journal:  Aging Dis       Date:  2020-12-01       Impact factor: 6.745

6.  Correlation between Alzheimer's disease and type 2 diabetes using non-negative matrix factorization.

Authors:  Yeonwoo Chung; Hyunju Lee
Journal:  Sci Rep       Date:  2021-07-27       Impact factor: 4.379

7.  An Integrative Approach for Mapping Differentially Expressed Genes and Network Components Using Novel Parameters to Elucidate Key Regulatory Genes in Colorectal Cancer.

Authors:  Manika Sehgal; Rajinder Gupta; Ahmed Moussa; Tiratha Raj Singh
Journal:  PLoS One       Date:  2015-07-29       Impact factor: 3.240

  7 in total

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