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

Panigrahi, Priya P.; Singh, Tiratha Raj

doi:10.1016/j.jtbi.2013.06.013

Cited by 30 publications

(9 citation statements)

References 79 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, Panigrahi and Singh applied an integrative systems biology approach to AD pathway and regulatory network analysis [9]. They identified 26 novel genes and variants associated with AD and ageing and some coexpression networks.…”

Section: Resultsmentioning

confidence: 99%

“…Liang et al integrated gene expression profiles with prior protein-protein interaction (PPI) network information to reveal significantly perturbed subnetwork in 6 brain regions [8]. Panigrahi and Singh identified novel gene variants in various biological processes, new information for network motif, groups of transcriptional factors (TFs), and miRNA targets to demonstrate that there are extensive links between AD and ageing (AG) [9]. …”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic Regulatory Network Reconstruction for Alzheimer’s Disease Based on Matrix Decomposition Techniques

Kong

Mou

Zhi

et al. 2014

Computational and Mathematical Methods in Medicine

View full text Add to dashboard Cite

Alzheimer's disease (AD) is the most common form of dementia and leads to irreversible neurodegenerative damage of the brain. Finding the dynamic responses of genes, signaling proteins, transcription factor (TF) activities, and regulatory networks of the progressively deteriorative progress of AD would represent a significant advance in discovering the pathogenesis of AD. However, the high throughput technologies of measuring TF activities are not yet available on a genome-wide scale. In this study, based on DNA microarray gene expression data and a priori information of TFs, network component analysis (NCA) algorithm is applied to determining the TF activities and regulatory influences on TGs of incipient, moderate, and severe AD. Based on that, the dynamical gene regulatory networks of the deteriorative courses of AD were reconstructed. To select significant genes which are differentially expressed in different courses of AD, independent component analysis (ICA), which is better than the traditional clustering methods and can successfully group one gene in different meaningful biological processes, was used. The molecular biological analysis showed that the changes of TF activities and interactions of signaling proteins in mitosis, cell cycle, immune response, and inflammation play an important role in the deterioration of AD.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic Regulatory Network Reconstruction for Alzheimer’s Disease Based on Matrix Decomposition Techniques

Kong

Mou

Zhi

et al. 2014

Computational and Mathematical Methods in Medicine

View full text Add to dashboard Cite

show abstract

“…mlh1 , msh2 , msh3 and msh6 of MSI pathway contributes to hereditary non-polyposis colorectal cancer (HNPCC) and CRC. Therefore, investigating important up and down regulated genes may deduce markers for CRC as observed in other studies for different diseases [ 22 ]. Further, a comprehensive perceptive on the genes and related pathways is required for designing specific and effective therapies for CRC [ 23 ].…”

Section: Introductionmentioning

confidence: 99%

“…But, the ultimate challenge lies in extracting vital biological information or markers from this amalgamation of data [ 24 ]. The DNA microarray technique not only provides a valuable measure for estimating expression of thousand genes at once but also offers vital molecular clues regarding mechanisms underlying the pathophysiology of disease [ 22 , 25 ]. Subsequently, the strategy we pursued includes identification of biologically significant genes and elucidation of key patterns or motifs formed by these candidate genes which governs the functional impact of various biological processes in CRC.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2015

Self Cite

View full text Add to dashboard Cite

For examining the intricate biological processes concerned with colorectal cancer (CRC), a systems biology approach integrating several biological components and other influencing factors is essential to understand. We performed a comprehensive system level analysis for CRC which assisted in unravelling crucial network components and many regulatory elements through a coordinated view. Using this integrative approach, the perceptive of complexity hidden in a biological phenomenon is extensively simplified. The microarray analyses facilitated differential expression of 631 significant genes employed in the progression of disease and supplied interesting associated up and down regulated genes like jun, fos and mapk1. The transcriptional regulation of these genes was deliberated widely by examining transcription factors such as hnf4, nr2f1, znf219 and dr1 which directly influence the expression. Further, interactions of these genes/proteins were evaluated and crucial network motifs were detected to associate with the pathophysiology of CRC. The available standard statistical parameters such as z-score, p-value and significance profile were explored for the identification of key signatures from CRC pathway whereas a few novel parameters representing over-represented structures were also designed in the study. The applied approach revealed 5 key genes i.e. kras, araf, pik3r5, ralgds and akt3 via our novel designed parameters illustrating high statistical significance. These novel parameters can assist in scrutinizing candidate markers for diseases having known biological pathways. Further, investigating and targeting these proposed genes for experimental validations, instead being spellbound by the complicated pathway will certainly endow valuable insight in a well-timed systematic understanding of CRC.

show abstract

“…Mt DNA has been extensively studied for evidences of selection in the last several years. Several interesting functional and evolutionary facts were reveled after analyzing complete mt genomic sequences during last two decades [1][2][3][4][5][6][7]. With the availability of thousands of complete mt genomes, comparative mt genomics promises to be the basis for distinct patterns and processes of functional genomics and molecular evolution of mitochondria and associated biological entities.…”

Section: Introductionmentioning

confidence: 99%

Mitochondrial Genomes and Frameshift Mutations: Hidden Stop Codons, their Functional Consequences and Disease Associations

Singh¹

2013

Int J Genomic Med

View full text Add to dashboard Cite

Reprogramming of mRNA translation by localized alterations in the standard translational rules is termed as recoding. Frameshifting is one class of recoding and defined as protein translations that start not at the first, but either at the second (+1 frameshift) or the third (-1 frameshift) nucleotide of the codon. Apparently, most frameshifts would yield nonfunctional proteins. Therefore frameshifts lead to waste of energy, resources and activity of the biosynthetic machinery. In addition, some peptides synthesized after frameshifts are most likely cytotoxic. Coding sequences lack stop codons, but many stop codons generated due to frameshifted sequences, termed off-frame stops or hidden stop codons. These hidden stops terminate frame-shifted translation, potentially decreasing energy, and resource waste on nonfunctional proteins. Frameshift mutations for the sake of mitochondrial genomes were evaluated and results support this putative ancient adaptive event for the selection of codons that can be part of hidden stop codons. Mitochondrial genomic data analyses support this fact as most of the correlations between hidden stops and various functional and evolutionary parameters were positive. Association of frameshift mutations with many diseases is also being studied to represent the biological significance of this putative event. It is estimated that this kind of study will reveal momentous correlation between frameshift mutations and their biological consequences.

show abstract

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

Cited by 30 publications

References 79 publications

Dynamic Regulatory Network Reconstruction for Alzheimer’s Disease Based on Matrix Decomposition Techniques

Dynamic Regulatory Network Reconstruction for Alzheimer’s Disease Based on Matrix Decomposition Techniques

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

Mitochondrial Genomes and Frameshift Mutations: Hidden Stop Codons, their Functional Consequences and Disease Associations

Contact Info

Product

Resources

About