Infectious Disease

CapsNet-COVID19: Lung CT image classification method based on CapsNet model.

The outbreak of the Corona Virus Disease 2019 (COVID-19) has posed a serious threat to human health and life around the world. As the number of COVID-19 cases continues to increase, many countries are facing problems such as errors in nucleic acid testing (RT-PCR), shortage of testing reagents, and lack of testing personnel. In order to solve such problems, it is necessary to propose a more accura...

Accelerating the discovery of antifungal peptides using deep temporal convolutional networks.

The application of machine intelligence in biological sciences has led to the development of several automated tools, thus enabling rapid drug discovery. Adding to this development is the ongoing COVID-19 pandemic, due to which researchers working in the field of artificial intelligence have acquired an active interest in finding machine learning-guided solutions for diseases like mucormycosis, wh...

Adapt-Kcr: a novel deep learning framework for accurate prediction of lysine crotonylation sites based on learning embedding features and attention architecture.

Protein lysine crotonylation (Kcr) is an important type of posttranslational modification that is associated with a wide range of biological processes...

Machine Learning Used to Compare the Diagnostic Accuracy of Risk Factors, Clinical Signs and Biomarkers and to Develop a New Prediction Model for Neonatal Early-onset Sepsis.

BACKGROUND: Current strategies for risk stratification and prediction of neonatal early-onset sepsis (EOS) are inefficient and lack diagnostic perform...

Enhancing sepsis management through machine learning techniques: A review.

Sepsis is a major public health problem and a leading cause of death in the world, where delay in the beginning of treatment, along with clinical guid...

Deeplasmid: deep learning accurately separates plasmids from bacterial chromosomes.

Plasmids are mobile genetic elements that play a key role in microbial ecology and evolution by mediating horizontal transfer of important genes, such...

Rapid SARS-CoV-2 Inactivation in a Simulated Hospital Room Using a Mobile and Autonomous Robot Emitting Ultraviolet-C Light.

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) since 2019 has made mask-wearing, physical distancing, hygiene, and disinfe...

Virtifier: a deep learning-based identifier for viral sequences from metagenomes.

MOTIVATION: Viruses, the most abundant biological entities on earth, are important components of microbial communities, and as major human pathogens, ...

Gray-Level Co-occurrence Matrix Analysis for the Detection of Discrete, Ethanol-Induced, Structural Changes in Cell Nuclei: An Artificial Intelligence Approach.

Gray-level co-occurrence matrix (GLCM) analysis is a contemporary and innovative computational method for the assessment of textural patterns, applica...

Automated extraction of genes associated with antibiotic resistance from the biomedical literature.

The detection of bacterial antibiotic resistance phenotypes is important when carrying out clinical decisions for patient treatment. Conventional phen...

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

MOTIVATION: The Estimation of Model Accuracy problem is a cornerstone problem in the field of Bioinformatics. As of CASP14, there are 79 global QA met...

Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2.

Coronavirus disease 2019 (COVID-19) has impacted public health as well as societal and economic well-being. In the last two decades, various predictio...

Impact of computational approaches in the fight against COVID-19: an AI guided review of 17 000 studies.

SARS-CoV-2 caused the first severe pandemic of the digital era. Computational approaches have been ubiquitously used in an attempt to timely and effec...

sAMP-PFPDeep: Improving accuracy of short antimicrobial peptides prediction using three different sequence encodings and deep neural networks.

Short antimicrobial peptides (sAMPs) belong to a significant repertoire of antimicrobial agents and are known to possess enhanced antimicrobial activi...

Computational anti-COVID-19 drug design: progress and challenges.

Vaccines have made gratifying progress in preventing the 2019 coronavirus disease (COVID-19) pandemic. However, the emergence of variants, especially ...

Heavy chain sequence-based classifier for the specificity of human antibodies.

Antibodies specifically bind to antigens and are an essential part of the immune system. Hence, antibodies are powerful tools in research and diagnost...

A deep learning method for repurposing antiviral drugs against new viruses via multi-view nonnegative matrix factorization and its application to SARS-CoV-2.

The outbreak of COVID-19 caused by SARS-coronavirus (CoV)-2 has made millions of deaths since 2019. Although a variety of computational methods have b...

Active disease-related compound identification based on capsule network.

Pneumonia, especially corona virus disease 2019 (COVID-19), can lead to serious acute lung injury, acute respiratory distress syndrome, multiple organ...

Increasing a microscope's effective field of view via overlapped imaging and machine learning.

This work demonstrates a multi-lens microscopic imaging system that overlaps multiple independent fields of view on a single sensor for high-efficienc...

The reactome pathway knowledgebase 2022.

The Reactome Knowledgebase (https://reactome.org), an Elixir core resource, provides manually curated molecular details across a broad range of physio...