AIMC Topic: Software

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AntiVPP 1.0: A portable tool for prediction of antiviral peptides.

Computers in biology and medicine
Viruses are worldwide pathogens with a high impact on the human population. Despite the constant efforts to fight viral infections, there is a need to discover and design new drug candidates. Antiviral peptides are molecules with confirmed activity a...

SignalP 5.0 improves signal peptide predictions using deep neural networks.

Nature biotechnology
Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish ...

ELM-MHC: An Improved MHC Identification Method with Extreme Learning Machine Algorithm.

Journal of proteome research
The major histocompatibility complex (MHC) is a term for all gene groups of a major histocompatibility antigen. It binds to peptide chains derived from pathogens and displays pathogens on the cell surface to facilitate T-cell recognition and perform ...

DeepUbi: a deep learning framework for prediction of ubiquitination sites in proteins.

BMC bioinformatics
BACKGROUND: Protein ubiquitination occurs when the ubiquitin protein binds to a target protein residue of lysine (K), and it is an important regulator of many cellular functions, such as signal transduction, cell division, and immune reactions, in eu...

CirGO: an alternative circular way of visualising gene ontology terms.

BMC bioinformatics
BACKGROUND: Prioritisation of gene ontology terms from differential gene expression analyses in a two-dimensional format remains a challenge with exponentially growing data volumes. Typically, gene ontology terms are represented as tree-maps that enc...

MoDeSuS: A Machine Learning Tool for Selection of Molecular Descriptors in QSAR Studies Applied to Molecular Informatics.

BioMed research international
The selection of the most relevant molecular descriptors to describe a target variable in the context of QSAR (Quantitative Structure-Activity Relationship) modelling is a challenging combinatorial optimization problem. In this paper, a novel softwar...

FunMappOne: a tool to hierarchically organize and visually navigate functional gene annotations in multiple experiments.

BMC bioinformatics
BACKGROUND: Functional annotation of genes is an essential step in omics data analysis. Multiple databases and methods are currently available to summarize the functions of sets of genes into higher level representations, such as ontologies and molec...

Machine Learning Consensus To Predict the Binding to the Androgen Receptor within the CoMPARA Project.

Journal of chemical information and modeling
The nuclear androgen receptor (AR) is one of the most relevant biological targets of Endocrine Disrupting Chemicals (EDCs), which produce adverse effects by interfering with hormonal regulation and endocrine system functioning. This paper describes n...

Vision-aided brain-machine interface training system for robotic arm control and clinical application on two patients with cervical spinal cord injury.

Biomedical engineering online
BACKGROUND: While spontaneous robotic arm control using motor imagery has been reported, most previous successful cases have used invasive approaches with advantages in spatial resolution. However, still many researchers continue to investigate metho...

DeepPVP: phenotype-based prioritization of causative variants using deep learning.

BMC bioinformatics
BACKGROUND: Prioritization of variants in personal genomic data is a major challenge. Recently, computational methods that rely on comparing phenotype similarity have shown to be useful to identify causative variants. In these methods, pathogenicity ...