AIMC Topic: Computational Biology

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Eleven quick tips for data cleaning and feature engineering.

PLoS computational biology
Applying computational statistics or machine learning methods to data is a key component of many scientific studies, in any field, but alone might not be sufficient to generate robust and reliable outcomes and results. Before applying any discovery m...

Molecular modeling of C1-inhibitor as SARS-CoV-2 target identified from the immune signatures of multiple tissues: An integrated bioinformatics study.

Cell biochemistry and function
The expeditious transmission of the severe acute respiratory coronavirus 2 (SARS-CoV-2), a strain of COVID-19, crumbled the global economic strength and caused a veritable collapse in health infrastructure. The molecular modeling of the novel coronav...

Novel machine learning approaches revolutionize protein knowledge.

Trends in biochemical sciences
Breakthrough methods in machine learning (ML), protein structure prediction, and novel ultrafast structural aligners are revolutionizing structural biology. Obtaining accurate models of proteins and annotating their functions on a large scale is no l...

miRBind: A Deep Learning Method for miRNA Binding Classification.

Genes
The binding of microRNAs (miRNAs) to their target sites is a complex process, mediated by the Argonaute (Ago) family of proteins. The prediction of miRNA:target site binding is an important first step for any miRNA target prediction algorithm. To dat...

Finding lncRNA-Protein Interactions Based on Deep Learning With Dual-Net Neural Architecture.

IEEE/ACM transactions on computational biology and bioinformatics
The identification of lncRNA-protein interactions (LPIs) is important to understand the biological functions and molecular mechanisms of lncRNAs. However, most computational models are evaluated on a unique dataset, thereby resulting in prediction bi...

New Labeling Methods for Deep Learning Real-Valued Inter-Residue Distance Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
BACKGROUND: Much of the recent success in protein structure prediction has been a result of accurate protein contact prediction-a binary classification problem. Dozens of methods, built from various types of machine learning and deep learning algorit...

A Novel Method for Inferring Chemical Compounds With Prescribed Topological Substructures Based on Integer Programming.

IEEE/ACM transactions on computational biology and bioinformatics
Drug discovery is one of the major goals of computational biology and bioinformatics. A novel framework has recently been proposed for the design of chemical graphs using both artificial neural networks (ANNs) and mixed integer linear programming (MI...

IGNSCDA: Predicting CircRNA-Disease Associations Based on Improved Graph Convolutional Network and Negative Sampling.

IEEE/ACM transactions on computational biology and bioinformatics
Accumulating evidences have shown that circRNA plays an important role in human diseases. It can be used as potential biomarker for diagnose and treatment of disease. Although some computational methods have been proposed to predict circRNA-disease a...

Predicting N6-Methyladenosine Sites in Multiple Tissues of Mammals through Ensemble Deep Learning.

International journal of molecular sciences
N6-methyladenosine (mA) is the most abundant within eukaryotic messenger RNA modification, which plays an essential regulatory role in the control of cellular functions and gene expression. However, it remains an outstanding challenge to detect mRNA ...