AIMC Topic: Computational Biology

Clear Filters Showing 2411 to 2420 of 4583 articles

Time-resolved evaluation of compound repositioning predictions on a text-mined knowledge network.

BMC bioinformatics
BACKGROUND: Computational compound repositioning has the potential for identifying new uses for existing drugs, and new algorithms and data source aggregation strategies provide ever-improving results via in silico metrics. However, even with these a...

Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning.

Nature methods
Predicting interactions between proteins and other biomolecules solely based on structure remains a challenge in biology. A high-level representation of protein structure, the molecular surface, displays patterns of chemical and geometric features th...

Supervised and unsupervised algorithms for bioinformatics and data science.

Progress in biophysics and molecular biology
Bioinformatics refers to an ever evolving huge field of research based on millions of algorithms, designated to several data banks. Such algorithms are either supervised or unsupervised. In this article, a detailed overview of the supervised and unsu...

Integrated structural modeling and super-resolution imaging resolve GPCR oligomers.

Progress in molecular biology and translational science
Formation of G protein-coupled receptors (GPCRs) dimers and higher order oligomers represents a key mechanism in pleiotropic signaling, yet how individual protomers function within oligomers remains poorly understood. For the Class A/rhodopsin subfam...

Artificial Intelligence Steering Molecular Therapy in the Absence of Information on Target Structure and Regulation.

Journal of chemical information and modeling
Protein associations are at the core of biological activity, and the drug-based disruption of dysfunctional associations poses a major challenge to targeted therapy. The problem becomes daunting when the structure and regulated modulation of the comp...

Identifying undetected dementia in UK primary care patients: a retrospective case-control study comparing machine-learning and standard epidemiological approaches.

BMC medical informatics and decision making
BACKGROUND: Identifying dementia early in time, using real world data, is a public health challenge. As only two-thirds of people with dementia now ultimately receive a formal diagnosis in United Kingdom health systems and many receive it late in the...

CDSeq: A novel complete deconvolution method for dissecting heterogeneous samples using gene expression data.

PLoS computational biology
Quantifying cell-type proportions and their corresponding gene expression profiles in tissue samples would enhance understanding of the contributions of individual cell types to the physiological states of the tissue. Current approaches that address ...

Dissection of gene expression datasets into clinically relevant interaction signatures via high-dimensional correlation maximization.

Nature communications
Gene expression is controlled by many simultaneous interactions, frequently measured collectively in biology and medicine by high-throughput technologies. It is a highly challenging task to infer from these data the generating effects and cooperating...

RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning.

Nature communications
The majority of our human genome transcribes into noncoding RNAs with unknown structures and functions. Obtaining functional clues for noncoding RNAs requires accurate base-pairing or secondary-structure prediction. However, the performance of such p...

Machine Learning Approaches for the Prioritization of Genomic Variants Impacting Pre-mRNA Splicing.

Cells
Defects in pre-mRNA splicing are frequently a cause of Mendelian disease. Despite the advent of next-generation sequencing, allowing a deeper insight into a patient's variant landscape, the ability to characterize variants causing splicing defects ha...