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Evolutionarily informed deep learning methods for predicting relative transcript abundance from DNA sequence.

Proceedings of the National Academy of Sciences of the United States of America
Deep learning methodologies have revolutionized prediction in many fields and show potential to do the same in molecular biology and genetics. However, applying these methods in their current forms ignores evolutionary dependencies within biological ...

A multi-task convolutional deep neural network for variant calling in single molecule sequencing.

Nature communications
The accurate identification of DNA sequence variants is an important, but challenging task in genomics. It is particularly difficult for single molecule sequencing, which has a per-nucleotide error rate of ~5-15%. Meeting this demand, we developed Cl...

Adaboost-SVM-based probability algorithm for the prediction of all mature miRNA sites based on structured-sequence features.

Scientific reports
The significant role of microRNAs (miRNAs) in various biological processes and diseases has been widely studied and reported in recent years. Several computational methods associated with mature miRNA identification suffer various limitations involvi...

Double-integrated mimic enzymes for the visual screening of Microcystin-LR: Copper hydroxide nanozyme and G-quadruplex/hemin DNAzyme.

Analytica chimica acta
Recently, mimic enzymes have obtained particular interest by their high activity, stability, and biocompatibility. In this work, by coupling copper hydroxide nanozyme and G-quadruplex/hemin DNAzyme to form a double-integrated mimic enzyme, a visual, ...

SFPEL-LPI: Sequence-based feature projection ensemble learning for predicting LncRNA-protein interactions.

PLoS computational biology
LncRNA-protein interactions play important roles in post-transcriptional gene regulation, poly-adenylation, splicing and translation. Identification of lncRNA-protein interactions helps to understand lncRNA-related activities. Existing computational ...

Smart Plasmonic Nanorobot for Real-Time Monitoring Cytochrome c Release and Cell Acidification in Apoptosis during Electrostimulation.

Analytical chemistry
Cytochrome c (Cyt c) release and cellular pH change are two important mediators of apoptosis. Effective methods to regulate or monitor such two events are therefore highly desired for apoptosis research and cancer cell therapy. Herein, we exploited e...

Deep learning architectures for prediction of nucleosome positioning from sequences data.

BMC bioinformatics
BACKGROUND: Nucleosomes are DNA-histone complex, each wrapping about 150 pairs of double-stranded DNA. Their function is fundamental for one of the primary functions of Chromatin i.e. packing the DNA into the nucleus of the Eukaryote cells. Several b...

Predictable and precise template-free CRISPR editing of pathogenic variants.

Nature
Following Cas9 cleavage, DNA repair without a donor template is generally considered stochastic, heterogeneous and impractical beyond gene disruption. Here, we show that template-free Cas9 editing is predictable and capable of precise repair to a pre...

CamurWeb: a classification software and a large knowledge base for gene expression data of cancer.

BMC bioinformatics
BACKGROUND: The high growth of Next Generation Sequencing data currently demands new knowledge extraction methods. In particular, the RNA sequencing gene expression experimental technique stands out for case-control studies on cancer, which can be ad...

Machine Learning for detection of viral sequences in human metagenomic datasets.

BMC bioinformatics
BACKGROUND: Detection of highly divergent or yet unknown viruses from metagenomics sequencing datasets is a major bioinformatics challenge. When human samples are sequenced, a large proportion of assembled contigs are classified as "unknown", as conv...