AIMC Topic: Databases, Nucleic Acid
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lncRNA_Mdeep: An Alignment-Free Predictor for Distinguishing Long Non-Coding RNAs from Protein-Coding Transcripts by Multimodal Deep Learning.
International journal of molecular sciences
Jul 23, 2020
Long non-coding RNAs (lncRNAs) play crucial roles in diverse biological processes and human complex diseases. Distinguishing lncRNAs from protein-coding transcripts is a fundamental step for analyzing the lncRNA functional mechanism. However, the exp...
Deep Learning Based Drug Screening for Novel Coronavirus 2019-nCov.
Interdisciplinary sciences, computational life sciences
Jun 1, 2020
A novel coronavirus, called 2019-nCoV, was recently found in Wuhan, Hubei Province of China, and now is spreading across China and other parts of the world. Although there are some drugs to treat 2019-nCoV, there is no proper scientific evidence abou...
Pandemics
COVID-19
SARS-CoV-2
Drug Design
Humans
Structural Homology, Protein
Betacoronavirus
Pneumonia, Viral
Coronavirus 3C Proteases
Sequence Alignment
Cysteine Endopeptidases
Databases, Pharmaceutical
Amino Acid Sequence
Coronavirus Infections
Models, Molecular
Viral Nonstructural Proteins
Deep Learning
Ligands
Catalytic Domain
Molecular Dynamics Simulation
Databases, Nucleic Acid
User-Computer Interface
Drug Evaluation, Preclinical
Oligopeptides
Antiviral Agents
CNN-Peaks: ChIP-Seq peak detection pipeline using convolutional neural networks that imitate human visual inspection.
Scientific reports
May 13, 2020
ChIP-seq is one of the core experimental resources available to understand genome-wide epigenetic interactions and identify the functional elements associated with diseases. The analysis of ChIP-seq data is important but poses a difficult computation...
DDBJ Data Analysis Challenge: a machine learning competition to predict Arabidopsis chromatin feature annotations from DNA sequences.
Genes & genetic systems
Mar 26, 2020
Recently, the prospect of applying machine learning tools for automating the process of annotation analysis of large-scale sequences from next-generation sequencers has raised the interest of researchers. However, finding research collaborators with ...
An Intelligent Optimization Algorithm for Constructing a DNA Storage Code: NOL-HHO.
International journal of molecular sciences
Mar 22, 2020
The high density, large capacity, and long-term stability of DNA molecules make them an emerging storage medium that is especially suitable for the long-term storage of large datasets. The DNA sequences used in storage need to consider relevant const...
Modeling aspects of the language of life through transfer-learning protein sequences.
BMC bioinformatics
Dec 17, 2019
BACKGROUND: Predicting protein function and structure from sequence is one important challenge for computational biology. For 26 years, most state-of-the-art approaches combined machine learning and evolutionary information. However, for some applica...
CDSeq: A novel complete deconvolution method for dissecting heterogeneous samples using gene expression data.
PLoS computational biology
Dec 2, 2019
Quantifying cell-type proportions and their corresponding gene expression profiles in tissue samples would enhance understanding of the contributions of individual cell types to the physiological states of the tissue. Current approaches that address ...
Analysis of defective pathways and drug repositioning in Multiple Sclerosis via machine learning approaches.
Computers in biology and medicine
Oct 9, 2019
BACKGROUND: Although some studies show that there could be a genetic predisposition to develop Multiple Sclerosis (MS), attempts to find genetic signatures related to MS diagnosis and development are extremely rare.
PTPD: predicting therapeutic peptides by deep learning and word2vec.
BMC bioinformatics
Sep 6, 2019
*: Background In the search for therapeutic peptides for disease treatments, many efforts have been made to identify various functional peptides from large numbers of peptide sequence databases. In this paper, we propose an effective computational mo...
Identification of the expressome by machine learning on omics data.
Proceedings of the National Academy of Sciences of the United States of America
Aug 16, 2019
Accurate annotation of plant genomes remains complex due to the presence of many pseudogenes arising from whole-genome duplication-generated redundancy or the capture and movement of gene fragments by transposable elements. Machine learning on genome...
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