AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Mitochondrial Proteins

Showing 1 to 10 of 15 articles

Clear Filters

A novel deep learning-assisted hybrid network for plasmodium falciparum parasite mitochondrial proteins classification.

PloS one
Plasmodium falciparum is a parasitic protozoan that can cause malaria, which is a deadly disease. Therefore, the accurate identification of malaria parasite mitochondrial proteins is essential for understanding their functions and identifying novel d...

Application of Feature Selection and Deep Learning for Cancer Prediction Using DNA Methylation Markers.

Genes
DNA methylation is a process that can affect gene accessibility and therefore gene expression. In this study, a machine learning pipeline is proposed for the prediction of breast cancer and the identification of significant genes that contribute to t...

iTTCA-MFF: identifying tumor T cell antigens based on multiple feature fusion.

Immunogenetics
Cancer is a terrible disease, recent studies reported that tumor T cell antigens (TTCAs) may play a promising role in cancer treatment. Since experimental methods are still expensive and time-consuming, it is highly desirable to develop automatic com...

In-Pero: Exploiting Deep Learning Embeddings of Protein Sequences to Predict the Localisation of Peroxisomal Proteins.

International journal of molecular sciences
Peroxisomes are ubiquitous membrane-bound organelles, and aberrant localisation of peroxisomal proteins contributes to the pathogenesis of several disorders. Many computational methods focus on assigning protein sequences to subcellular compartments,...

TPpred3 detects and discriminates mitochondrial and chloroplastic targeting peptides in eukaryotic proteins.

Bioinformatics (Oxford, England)
MOTIVATION: Molecular recognition of N-terminal targeting peptides is the most common mechanism controlling the import of nuclear-encoded proteins into mitochondria and chloroplasts. When experimental information is lacking, computational methods can...

Human mitochondrial protein complexes revealed by large-scale coevolution analysis and deep learning-based structure modeling.

Bioinformatics (Oxford, England)
MOTIVATION: Recent development of deep-learning methods has led to a breakthrough in the prediction accuracy of 3D protein structures. Extending these methods to protein pairs is expected to allow large-scale detection of protein-protein interactions...

iDeepSubMito: identification of protein submitochondrial localization with deep learning.

Briefings in bioinformatics
Mitochondria are membrane-bound organelles containing over 1000 different proteins involved in mitochondrial function, gene expression and metabolic processes. Accurate localization of those proteins in the mitochondrial compartments is critical to t...

DeepPred-SubMito: A Novel Submitochondrial Localization Predictor Based on Multi-Channel Convolutional Neural Network and Dataset Balancing Treatment.

International journal of molecular sciences
Mitochondrial proteins are physiologically active in different compartments, and their abnormal location will trigger the pathogenesis of human mitochondrial pathologies. Correctly identifying submitochondrial locations can provide information for di...

MMPdb and MitoPredictor: Tools for facilitating comparative analysis of animal mitochondrial proteomes.

Mitochondrion
Data on experimentally-characterized animal mitochondrial proteomes (mt-proteomes) are limited to a few model organisms and are scattered across multiple databases, impeding a comparative analysis. We developed two resources to address these problems...