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Viral Proteins

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Super.Complex: A supervised machine learning pipeline for molecular complex detection in protein-interaction networks.

PloS one
Characterization of protein complexes, i.e. sets of proteins assembling into a single larger physical entity, is important, as such assemblies play many essential roles in cells such as gene regulation. From networks of protein-protein interactions, ...

Machine learning prediction of antiviral-HPV protein interactions for anti-HPV pharmacotherapy.

Scientific reports
Persistent infection with high-risk types Human Papillomavirus could cause diseases including cervical cancers and oropharyngeal cancers. Nonetheless, so far there is no effective pharmacotherapy for treating the infection from high-risk HPV types, a...

ZoomQA: residue-level protein model accuracy estimation with machine learning on sequential and 3D structural features.

Briefings in bioinformatics
MOTIVATION: The Estimation of Model Accuracy problem is a cornerstone problem in the field of Bioinformatics. As of CASP14, there are 79 global QA methods, and a minority of 39 residue-level QA methods with very few of them working on protein complex...

PhageLeads: Rapid Assessment of Phage Therapeutic Suitability Using an Ensemble Machine Learning Approach.

Viruses
The characterization of therapeutic phage genomes plays a crucial role in the success rate of phage therapies. There are three checkpoints that need to be examined for the selection of phage candidates, namely, the presence of temperate markers, anti...

Potential SARS-CoV-2 nonstructural proteins inhibitors: drugs repurposing with drug-target networks and deep learning.

Frontiers in bioscience (Landmark edition)
BACKGROUND: In the current COVID-19 pandemic, with an absence of approved drugs and widely accessible vaccines, repurposing existing drugs is vital to quickly developing a treatment for the disease.

Benchmarking machine learning robustness in Covid-19 genome sequence classification.

Scientific reports
The rapid spread of the COVID-19 pandemic has resulted in an unprecedented amount of sequence data of the SARS-CoV-2 genome-millions of sequences and counting. This amount of data, while being orders of magnitude beyond the capacity of traditional ap...

High-throughput Kinetics using capillary Electrophoresis and Robotics (HiKER) platform used to study T7, T3, and Sp6 RNA polymerase misincorporation.

PloS one
T7 RNA Polymerase (RNAP) is a widely used enzyme with recent applications in the production of RNA vaccines. For over 50 years denaturing sequencing gels have been used as key analysis tools for probing the nucleotide addition mechanisms of T7 RNAP a...

DeePhafier: a phage lifestyle classifier using a multilayer self-attention neural network combining protein information.

Briefings in bioinformatics
Bacteriophages are the viruses that infect bacterial cells. They are the most diverse biological entities on earth and play important roles in microbiome. According to the phage lifestyle, phages can be divided into the virulent phages and the temper...

Predicting viral proteins that evade the innate immune system: a machine learning-based immunoinformatics tool.

BMC bioinformatics
Viral proteins that evade the host's innate immune response play a crucial role in pathogenesis, significantly impacting viral infections and potential therapeutic strategies. Identifying these proteins through traditional methods is challenging and ...

Prediction of viral oncoproteins through the combination of generative adversarial networks and machine learning techniques.

Scientific reports
Viral oncoproteins play crucial roles in transforming normal cells into cancer cells, representing a significant factor in the etiology of various cancers. Traditionally, identifying these oncoproteins is both time-consuming and costly. With advancem...