AIMC Topic: Gene Expression Profiling
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Effect of abiotic and biotic stress factors analysis using machine learning methods in zebrafish.
Comparative biochemistry and physiology. Part D, Genomics & proteomics
Nov 11, 2017
In order to understand the mechanisms underlying stress responses, meta-analysis of transcriptome is made to identify differentially expressed genes (DEGs) and their biological, molecular and cellular mechanisms in response to stressors. The present ...
A Bi-Objective RNN Model to Reconstruct Gene Regulatory Network: A Modified Multi-Objective Simulated Annealing Approach.
IEEE/ACM transactions on computational biology and bioinformatics
Nov 9, 2017
Gene Regulatory Network (GRN) is a virtual network in a cellular context of an organism, comprising a set of genes and their internal relationships to regulate protein production rate (gene expression level) of each other through coded proteins. Comp...
Incorporating gene ontology into fuzzy relational clustering of microarray gene expression data.
Bio Systems
Nov 4, 2017
The product of gene expression works together in the cell for each living organism in order to achieve different biological processes. Many proteins are involved in different roles depending on the environment of the organism for the functioning of t...
Structured Penalized Logistic Regression for Gene Selection in Gene Expression Data Analysis.
IEEE/ACM transactions on computational biology and bioinformatics
Oct 30, 2017
In gene expression data analysis, the problems of cancer classification and gene selection are closely related. Successfully selecting informative genes will significantly improve the classification performance. To identify informative genes from a l...
Comparative Analysis of the Cytology and Transcriptomes of the Cytoplasmic Male Sterility Line H276A and Its Maintainer Line H276B of Cotton (Gossypium barbadense L.).
International journal of molecular sciences
Oct 25, 2017
In this study, the tetrad stage of microspore development in a new cotton ( L.) cytoplasmic male sterility (CMS) line, H276A, was identified using paraffin sections at the abortion stage. To explore the molecular mechanism underlying CMS in cotton, a...
Identification of differentially expressed genes regulated by molecular signature in breast cancer-associated fibroblasts by bioinformatics analysis.
Archives of gynecology and obstetrics
Oct 23, 2017
OBJECTIVE: Breast cancer is a severe risk to public health and has adequately convoluted pathogenesis. Therefore, the description of key molecular markers and pathways is of much importance for clarifying the molecular mechanism of breast cancer-asso...
Predicting pathogenic genes for primary myelofibrosis based on a system‑network approach.
Molecular medicine reports
Oct 20, 2017
The aim of the present study was to predict pathogenic genes for primary myelofibrosis (PMF) using a system‑network approach by combining protein‑protein interaction (PPI) network and gene expression data with known pathogenic genes. PMF gene express...
Semantic biclustering for finding local, interpretable and predictive expression patterns.
BMC genomics
Oct 16, 2017
BACKGROUND: One of the major challenges in the analysis of gene expression data is to identify local patterns composed of genes showing coherent expression across subsets of experimental conditions. Such patterns may provide an understanding of under...
A novel machine learning approach reveals latent vascular phenotypes predictive of renal cancer outcome.
Scientific reports
Oct 16, 2017
Gene expression signatures are commonly used as predictive biomarkers, but do not capture structural features within the tissue architecture. Here we apply a 2-step machine learning framework for quantitative imaging of tumor vasculature to derive a ...
Deep Learning-Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer.
Clinical cancer research : an official journal of the American Association for Cancer Research
Oct 5, 2017
Identifying robust survival subgroups of hepatocellular carcinoma (HCC) will significantly improve patient care. Currently, endeavor of integrating multi-omics data to explicitly predict HCC survival from multiple patient cohorts is lacking. To fill ...
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