AIMC Topic: Software

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Interpreting Gene Ontology Annotations Derived from Sequence Homology Methods.

Methods in molecular biology (Clifton, N.J.)
The Gene Ontology (GO) project describes the functions of the gene products of organisms from all kingdoms of life in a standardized way, enabling powerful analyses of experiments involving genome-wide analysis. The scientific literature is used to c...

AI-Assisted Processing Pipeline to Boost Protein Isoform Detection.

Methods in molecular biology (Clifton, N.J.)
Proteomics, the study of proteins within biological systems, has seen remarkable advancements in recent years, with protein isoform detection emerging as one of the next major frontiers. One of the primary challenges is achieving the necessary peptid...

Assessment of Protein-Protein Docking Models Using Deep Learning.

Methods in molecular biology (Clifton, N.J.)
Protein-protein interactions are involved in almost all processes in a living cell and determine the biological functions of proteins. To obtain mechanistic understandings of protein-protein interactions, the tertiary structures of protein complexes ...

Machine Learning Methods in Protein-Protein Docking.

Methods in molecular biology (Clifton, N.J.)
An exponential increase in the number of publications that address artificial intelligence (AI) usage in life sciences has been noticed in recent years, while new modeling techniques are constantly being reported. The potential of these methods is va...

DeepHLApan: A Deep Learning Approach for the Prediction of Peptide-HLA Binding and Immunogenicity.

Methods in molecular biology (Clifton, N.J.)
Neoantigens are crucial in distinguishing cancer cells from normal ones and play a significant role in cancer immunotherapy. The field of bioinformatics prediction for tumor neoantigens has rapidly developed, focusing on the prediction of peptide-HLA...

Deep Learning-Based HLA Allele Imputation Applicable to GWAS.

Methods in molecular biology (Clifton, N.J.)
Human leukocyte antigen (HLA) imputation is an essential step following genome-wide association study, particularly when putative associations in HLA genes are identified, to fully understand the genetic basis of human traits. Different HLA imputatio...

Using Artificial Intelligence to Interpret Clinical Flow Cytometry Datasets for Automated Disease Diagnosis and/or Monitoring.

Methods in molecular biology (Clifton, N.J.)
Flow cytometry (FC) is routinely used for hematological disease diagnosis and monitoring. Advancement in this technology allows us to measure an increasing number of markers simultaneously, generating complex high-dimensional datasets. However, curre...

Contribution of Artificial Intelligence to the Identification of Protein-Protein Interactions: A Case Study on PAR-3 and Its Partner Adapter Molecule Crk.

Methods in molecular biology (Clifton, N.J.)
Protein-protein interactions (PPIs) are known to be involved in most cellular functions, and a detailed knowledge of such interactions is essential for studying their role in normal and pathological conditions. Significant progress is being made in t...

Computational and Translational Fractal-Based Analysis in the Translational Neurosciences: An Overview.

Advances in neurobiology
After the previous sections on "Fractals: What and Why?," the last section of this book covers the software tools necessary to perform computational fractal-based analysis, with special emphasis on its applications into the neurosciences. The use of ...

Software that combines deep learning, 3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Ultrasound is one of the non-invasive techniques that are used in clinical diagnostics of carotid artery disease.