AIMC Topic: Computational Biology

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Deep Analysis of Mitochondria and Cell Health Using Machine Learning.

Scientific reports
There is a critical need for better analytical methods to study mitochondria in normal and diseased states. Mitochondrial image analysis is typically done on still images using slow manual methods or automated methods of limited types of features. Mi...

Word and Sentence Embedding Tools to Measure Semantic Similarity of Gene Ontology Terms by Their Definitions.

Journal of computational biology : a journal of computational molecular cell biology
The gene ontology (GO) database contains GO terms that describe biological functions of genes. Previous methods for comparing GO terms have relied on the fact that GO terms are organized into a tree structure. Under this paradigm, the locations of tw...

Tuning parameter estimation in SCAD-support vector machine using firefly algorithm with application in gene selection and cancer classification.

Computers in biology and medicine
In cancer classification, gene selection is one of the most important bioinformatics related topics. The selection of genes can be considered to be a variable selection problem, which aims to find a small subset of genes that has the most discriminat...

Integrating network topology, gene expression data and GO annotation information for protein complex prediction.

Journal of bioinformatics and computational biology
The prediction of protein complexes based on the protein interaction network is a fundamental task for the understanding of cellular life as well as the mechanisms underlying complex disease. A great number of methods have been developed to predict p...

A neural network based model effectively predicts enhancers from clinical ATAC-seq samples.

Scientific reports
Enhancers are cis-acting sequences that regulate transcription rates of their target genes in a cell-specific manner and harbor disease-associated sequence variants in cognate cell types. Many complex diseases are associated with enhancer malfunction...

Representations of regular and irregular shapes by deep Convolutional Neural Networks, monkey inferotemporal neurons and human judgments.

PLoS computational biology
Recent studies suggest that deep Convolutional Neural Network (CNN) models show higher representational similarity, compared to any other existing object recognition models, with macaque inferior temporal (IT) cortical responses, human ventral stream...

Heterogeneous Domain Adaptation for IHC Classification of Breast Cancer Subtypes.

IEEE/ACM transactions on computational biology and bioinformatics
Increasingly, multiple parallel omics datasets are collected from biological samples. Integrating these datasets for classification is an open area of research. Additionally, whilst multiple datasets may be available for the training samples, future ...

Improving Protein Gamma-Turn Prediction Using Inception Capsule Networks.

Scientific reports
Protein gamma-turn prediction is useful in protein function studies and experimental design. Several methods for gamma-turn prediction have been developed, but the results were unsatisfactory with Matthew correlation coefficients (MCC) around 0.2-0.4...

Prediction and functional analysis of prokaryote lysine acetylation site by incorporating six types of features into Chou's general PseAAC.

Journal of theoretical biology
Lysine acetylation is one of the most important types of protein post-translational modifications (PTM) that are widely involved in cellular regulatory processes. To fully understand the regulatory mechanism of acetylation, identification of acetylat...

A computational method for prediction of xylanase enzymes activity in strains of Bacillus subtilis based on pseudo amino acid composition features.

PloS one
Xylanases are hydrolytic enzymes which based on physicochemical properties, structure, mode of action and substrate specificities are classified into various glycoside hydrolase (GH) families. The purpose of this study is to show that the activity of...