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CGPS: A machine learning-based approach integrating multiple gene set analysis tools for better prioritization of biologically relevant pathways.

Journal of genetics and genomics = Yi chuan xue bao
Gene set enrichment (GSE) analyses play an important role in the interpretation of large-scale transcriptome datasets. Multiple GSE tools can be integrated into a single method as obtaining optimal results is challenging due to the plethora of GSE to...

Gene Ontology Enrichment Improves Performances of Functional Similarity of Genes.

Scientific reports
There exists a plethora of measures to evaluate functional similarity (FS) between genes, which is a widely used in many bioinformatics applications including detecting molecular pathways, identifying co-expressed genes, predicting protein-protein in...

iMethyl-STTNC: Identification of N-methyladenosine sites by extending the idea of SAAC into Chou's PseAAC to formulate RNA sequences.

Journal of theoretical biology
N- methyladenosine (mA) is a vital post-transcriptional modification, which adds another layer of epigenetic regulation at RNA level. It chemically modifies mRNA that effects protein expression. RNA sequence contains many genetic code motifs (GAC). A...

diploS/HIC: An Updated Approach to Classifying Selective Sweeps.

G3 (Bethesda, Md.)
Identifying selective sweeps in populations that have complex demographic histories remains a difficult problem in population genetics. We previously introduced a supervised machine learning approach, S/HIC, for finding both hard and soft selective s...

Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC.

Journal of theoretical biology
This study examines accurate and efficient computational method for identification of 5-methylcytosine sites in RNA modification. The occurrence of 5-methylcytosine (mC) plays a vital role in a number of biological processes. For better comprehension...

A machine learning model to determine the accuracy of variant calls in capture-based next generation sequencing.

BMC genomics
BACKGROUND: Next generation sequencing (NGS) has become a common technology for clinical genetic tests. The quality of NGS calls varies widely and is influenced by features like reference sequence characteristics, read depth, and mapping accuracy. Wi...

A novel strategy for retention prediction of nucleic acids with their sequence information in ion-pair reversed phase liquid chromatography.

Talanta
In this work, retention behaviors of oligonucleotides and double-stranded deoxyribonucleic acids (dsDNAs) have been investigated in ion-pair reversed-phase liquid chromatography (IP-RPLC). We demonstrated that classic linear solvent strength (LSS) mo...

Computational Prediction of Sigma-54 Promoters in Bacterial Genomes by Integrating Motif Finding and Machine Learning Strategies.

IEEE/ACM transactions on computational biology and bioinformatics
Sigma factor, as a unit of RNA polymerase holoenzyme, is a critical factor in the process of gene transcriptional regulation. It recognizes the specific DNA sites and brings the core enzyme of RNA polymerase to the upstream regions of target genes. T...

Enhanced prediction of recombination hotspots using input features extracted by class specific autoencoders.

Journal of theoretical biology
In yeast and in some mammals the frequencies of recombination are high in some genomic locations which are known as recombination hotspots and in the locations where the recombination is below average are consequently known as coldspots. Knowledge of...