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Computational Biology

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Interpretable machine learning-driven biomarker identification and validation for Alzheimer's disease.

Scientific reports
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by limited effective treatments, underscoring the critical need for early detection and diagnosis to improve intervention outcomes. This study integrates various bioinformatics me...

Porter 6: Protein Secondary Structure Prediction by Leveraging Pre-Trained Language Models (PLMs).

International journal of molecular sciences
Accurately predicting protein secondary structure (PSSP) is crucial for understanding protein function, which is foundational to advancements in drug development, disease treatment, and biotechnology. Researchers gain critical insights into protein f...

Topology-based protein classification: A deep learning approach.

Biochemical and biophysical research communications
Utilizing Artificial Intelligence (AI) in computational biology techniques could offer significant advantages in alleviating the growing workloads faced by structural biologists, especially with the emergence of big data. In this study, we employed D...

Improved enzyme functional annotation prediction using contrastive learning with structural inference.

Communications biology
Recent years have witnessed the remarkable progress of deep learning within the realm of scientific disciplines, yielding a wealth of promising outcomes. A prominent challenge within this domain has been the task of predicting enzyme function, a comp...

Machine learning mathematical models for incidence estimation during pandemics.

PLoS computational biology
Accurate estimates of the incidence of infectious diseases are key for the control of epidemics. However, healthcare systems are often unable to test the population exhaustively, especially when asymptomatic and paucisymptomatic cases are widespread;...

Predicting the infecting dengue serotype from antibody titre data using machine learning.

PLoS computational biology
The development of a safe and efficacious vaccine that provides immunity against all four dengue virus serotypes is a priority, and a significant challenge for vaccine development has been defining and measuring serotype-specific outcomes and correla...

Integrating machine learning with bioinformatics for predicting idiopathic pulmonary fibrosis prognosis: developing an individualized clinical prediction tool.

Experimental biology and medicine (Maywood, N.J.)
Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease with a poor prognosis. Its non-specific clinical symptoms make accurate prediction of disease progression challenging. This study aimed to develop molecular-level prognostic m...

Machine learning methods for predicting essential metabolic genes from Plasmodium falciparum genome-scale metabolic network.

PloS one
Essential genes are those whose presence is vital for a cell's survival and growth. Detecting these genes in disease-causing organisms is critical for various biological studies, including understanding microbe metabolism, engineering genetically mod...

Tumour purity assessment with deep learning in colorectal cancer and impact on molecular analysis.

The Journal of pathology
Tumour content plays a pivotal role in directing the bioinformatic analysis of molecular profiles such as copy number variation (CNV). In clinical application, tumour purity estimation (TPE) is achieved either through visual pathological review [conv...