Benchmarks in antimicrobial peptide prediction are biased due to the selection of negative data
Antimicrobial peptides (AMPs) are a heterogeneous group of short polypeptides that target
not only microorganisms but also viruses and cancer cells. Due to their lower selection for …
not only microorganisms but also viruses and cancer cells. Due to their lower selection for …
[HTML][HTML] Machine learning approaches for plant miRNA prediction: challenges, advancements, and future directions
Z Kuang, Y Zhao, X Yang - Agriculture Communications, 2023 - Elsevier
MicroRNA (miRNA) is an important regulator of gene expression in plants that functions to
regulate plant development and growth. Signature sequences and secondary structures that …
regulate plant development and growth. Signature sequences and secondary structures that …
MicroRNA-mediated bioengineering for climate-resilience in crops
Global projections on the climate change and the dynamic environmental perturbations
indicate severe impacts on food security in general, and crop yield, vigor and the quality of …
indicate severe impacts on food security in general, and crop yield, vigor and the quality of …
MiRNA–disease association prediction based on meta-paths
L Yu, Y Zheng, L Gao - Briefings in Bioinformatics, 2022 - academic.oup.com
Since miRNAs can participate in the posttranscriptional regulation of gene expression, they
may provide ideas for the development of new drugs or become new biomarkers for drug …
may provide ideas for the development of new drugs or become new biomarkers for drug …
miRe2e: a full end-to-end deep model based on transformers for prediction of pre-miRNAs
Motivation MicroRNAs (miRNAs) are small RNA sequences with key roles in the regulation
of gene expression at post-transcriptional level in different species. Accurate prediction of …
of gene expression at post-transcriptional level in different species. Accurate prediction of …
[HTML][HTML] Deep Learning for the discovery of new pre-miRNAs: Helping the fight against COVID-19
Abstract The Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) has been
recently found responsible for the pandemic outbreak of a novel coronavirus disease …
recently found responsible for the pandemic outbreak of a novel coronavirus disease …
Hybrid deep neural network for handling data imbalance in precursor MicroRNA
Over the last decade, the field of bioinformatics has been increasing rapidly. Robust
bioinformatics tools are going to play a vital role in future progress. Scientists working in the …
bioinformatics tools are going to play a vital role in future progress. Scientists working in the …
DeepCNV: a deep learning approach for authenticating copy number variations
JT Glessner, X Hou, C Zhong, J Zhang… - Briefings in …, 2021 - academic.oup.com
Copy number variations (CNVs) are an important class of variations contributing to the
pathogenesis of many disease phenotypes. Detecting CNVs from genomic data remains …
pathogenesis of many disease phenotypes. Detecting CNVs from genomic data remains …
High precision in microRNA prediction: A novel genome-wide approach with convolutional deep residual networks
MicroRNAs (miRNAs) are small non-coding RNAs that have a key role in the regulation of
gene expression. The importance of miRNAs is widely acknowledged by the community …
gene expression. The importance of miRNAs is widely acknowledged by the community …
miWords: transformer-based composite deep learning for highly accurate discovery of pre-miRNA regions across plant genomes
Discovering pre-microRNAs (miRNAs) is the core of miRNA discovery. Using traditional
sequence/structural features, many tools have been published to discover miRNAs …
sequence/structural features, many tools have been published to discover miRNAs …