AIMC Topic: Computational Biology

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Disease Gene Prediction by Integrating PPI Networks, Clinical RNA-Seq Data and OMIM Data.

IEEE/ACM transactions on computational biology and bioinformatics
Disease gene prediction is a challenging task that has a variety of applications such as early diagnosis and drug development. The existing machine learning methods suffer from the imbalanced sample issue because the number of known disease genes (po...

An Improved Binary Differential Evolution Algorithm for Feature Selection in Molecular Signatures.

Molecular informatics
The discovery of biomarkers from high-dimensional data is a very challenging task in cancer diagnoses. On the one hand, biomarker discovery is the so-called high-dimensional small-sample problem. On the other hand, these data are redundant and noisy....

ToBio: Global Pathway Similarity Search Based on Topological and Biological Features.

IEEE/ACM transactions on computational biology and bioinformatics
Pathway similarity search plays a vital role in the post-genomics era. Unfortunately, pathway similarity search involves the graph isomorphism problem which is NP-complete. Therefore, efficient search algorithms are desirable. In this work, we propos...

Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.

Proteins
In this study, we report the evaluation of the residue-residue contacts predicted by our three different methods in the CASP12 experiment, focusing on studying the impact of multiple sequence alignment, residue coevolution, and machine learning on co...

Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC.

Journal of theoretical biology
Predicting protein subcellular location with support vector machine has been a popular research area recently because of the dramatic explosion of bioinformation. Though substantial achievements have been obtained, few researchers considered the prob...

Structured Penalized Logistic Regression for Gene Selection in Gene Expression Data Analysis.

IEEE/ACM transactions on computational biology and bioinformatics
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...

Simultaneous refinement of inaccurate local regions and overall structure in the CASP12 protein model refinement experiment.

Proteins
Advances in protein model refinement techniques are required as diverse sources of protein structure information are available from low-resolution experiments or informatics-based computations such as cryo-EM, NMR, homology models, or predicted resid...

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
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...

Automatic recognition of therapy progress among children with autism.

Scientific reports
The article presents a research study on recognizing therapy progress among children with autism spectrum disorder. The progress is recognized on the basis of behavioural data gathered via five specially designed tablet games. Over 180 distinct param...

Identification of differentially expressed genes regulated by molecular signature in breast cancer-associated fibroblasts by bioinformatics analysis.

Archives of gynecology and obstetrics
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...