AIMC Topic: Computational Biology

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Prediction of HIV-1 protease cleavage site using a combination of sequence, structural, and physicochemical features.

BMC bioinformatics
BACKGROUND: The human immunodeficiency virus type 1 (HIV-1) aspartic protease is an important enzyme owing to its imperative part in viral development and a causative agent of deadliest disease known as acquired immune deficiency syndrome (AIDS). Dev...

Intelligent Noninvasive Diagnosis of Aneuploidy: Raw Values and Highly Imbalanced Dataset.

IEEE journal of biomedical and health informatics
The objective of this paper is to introduce a noninvasive diagnosis procedure for aneuploidy and to minimize the social and financial cost of prenatal diagnosis tests that are performed for fetal aneuploidies in an early stage of pregnancy. We propos...

Predicting MoRFs in protein sequences using HMM profiles.

BMC bioinformatics
BACKGROUND: Intrinsically Disordered Proteins (IDPs) lack an ordered three-dimensional structure and are enriched in various biological processes. The Molecular Recognition Features (MoRFs) are functional regions within IDPs that undergo a disorder-t...

Stable feature selection based on the ensemble L -norm support vector machine for biomarker discovery.

BMC genomics
BACKGROUND: Lately, biomarker discovery has become one of the most significant research issues in the biomedical field. Owing to the presence of high-throughput technologies, genomic data, such as microarray data and RNA-seq, have become widely avail...

Grouping miRNAs of similar functions via weighted information content of gene ontology.

BMC bioinformatics
BACKGROUND: Regulation mechanisms between miRNAs and genes are complicated. To accomplish a biological function, a miRNA may regulate multiple target genes, and similarly a target gene may be regulated by multiple miRNAs. Wet-lab knowledge of co-regu...

Gogadget: An R Package for Interpretation and Visualization of GO Enrichment Results.

Molecular informatics
Gene expression profiling followed by gene ontology (GO) term enrichment analysis can generate long lists of significant GO terms. To interpret these results and get biological insight in the data, filtering and rearranging these long lists of GO ter...

Toward amino acid typing for proteins in FFLUX.

Journal of computational chemistry
Continuing the development of the FFLUX, a multipolar polarizable force field driven by machine learning, we present a modern approach to atom-typing and building transferable models for predicting atomic properties in proteins. Amino acid atomic cha...

Recent Progress in Machine Learning-Based Methods for Protein Fold Recognition.

International journal of molecular sciences
Knowledge on protein folding has a profound impact on understanding the heterogeneity and molecular function of proteins, further facilitating drug design. Predicting the 3D structure (fold) of a protein is a key problem in molecular biology. Determi...

SnoReport 2.0: new features and a refined Support Vector Machine to improve snoRNA identification.

BMC bioinformatics
BACKGROUND: snoReport uses RNA secondary structure prediction combined with machine learning as the basis to identify the two main classes of small nucleolar RNAs, the box H/ACA snoRNAs and the box C/D snoRNAs. Here, we present snoReport 2.0, which s...