AIMC Topic: Software

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EDCNN: identification of genome-wide RNA-binding proteins using evolutionary deep convolutional neural network.

Bioinformatics (Oxford, England)
MOTIVATION: RNA-binding proteins (RBPs) are a group of proteins associated with RNA regulation and metabolism, and play an essential role in mediating the maturation, transport, localization and translation of RNA. Recently, Genome-wide RNA-binding e...

scMRA: a robust deep learning method to annotate scRNA-seq data with multiple reference datasets.

Bioinformatics (Oxford, England)
MOTIVATION: Single-cell RNA-seq (scRNA-seq) has been widely used to resolve cellular heterogeneity. After collecting scRNA-seq data, the natural next step is to integrate the accumulated data to achieve a common ontology of cell types and states. Thu...

ECO: the Evidence and Conclusion Ontology, an update for 2022.

Nucleic acids research
The Evidence and Conclusion Ontology (ECO) is a community resource that provides an ontology of terms used to capture the type of evidence that supports biomedical annotations and assertions. Consistent capture of evidence information with ECO allows...

The reactome pathway knowledgebase 2022.

Nucleic acids research
The Reactome Knowledgebase (https://reactome.org), an Elixir core resource, provides manually curated molecular details across a broad range of physiological and pathological biological processes in humans, including both hereditary and acquired dise...

LncRNAWiki 2.0: a knowledgebase of human long non-coding RNAs with enhanced curation model and database system.

Nucleic acids research
LncRNAWiki, a knowledgebase of human long non-coding RNAs (lncRNAs), has been rapidly expanded by incorporating more experimentally validated lncRNAs. Since it was built based on MediaWiki as its database system, it fails to manage data in a structur...

Tiara: deep learning-based classification system for eukaryotic sequences.

Bioinformatics (Oxford, England)
MOTIVATION: With a large number of metagenomic datasets becoming available, eukaryotic metagenomics emerged as a new challenge. The proper classification of eukaryotic nuclear and organellar genomes is an essential step toward a better understanding ...

Prediction of whole-cell transcriptional response with machine learning.

Bioinformatics (Oxford, England)
MOTIVATION: Applications in synthetic and systems biology can benefit from measuring whole-cell response to biochemical perturbations. Execution of experiments to cover all possible combinations of perturbations is infeasible. In this paper, we prese...

TGSA: protein-protein association-based twin graph neural networks for drug response prediction with similarity augmentation.

Bioinformatics (Oxford, England)
MOTIVATION: Drug response prediction (DRP) plays an important role in precision medicine (e.g. for cancer analysis and treatment). Recent advances in deep learning algorithms make it possible to predict drug responses accurately based on genetic prof...

DLAB: deep learning methods for structure-based virtual screening of antibodies.

Bioinformatics (Oxford, England)
MOTIVATION: Antibodies are one of the most important classes of pharmaceuticals, with over 80 approved molecules currently in use against a wide variety of diseases. The drug discovery process for antibody therapeutic candidates however is time- and ...