AIMC Topic: Computational Biology

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Bioinformatic analysis of related immune cell infiltration and key genes in the progression of osteonecrosis of the femoral head.

Frontiers in immunology
OBJECTIVE: Osteonecrosis of the femoral head (ONFH) is a common orthopedic condition that will prompt joint dysfunction, significantly impacting patients' quality of life. However, the specific pathogenic mechanisms underlying this disease remain elu...

Identification and validation of platelet-related diagnostic markers and potential drug screening in ischemic stroke by integrating comprehensive bioinformatics analysis and machine learning.

Frontiers in immunology
BACKGROUND: Ischemic stroke (IS), caused by blood and oxygen deprivation due to cerebral thrombosis, has links to activated and aggregated platelets. Discovering platelet-related biomarkers, developing diagnostic models, and screening antiplatelet dr...

Prediction of protein structure and AI.

Journal of human genetics
AlphaFold, an artificial intelligence (AI)-based tool for predicting the 3D structure of proteins, is now widely recognized for its high accuracy and versatility in the folding of human proteins. AlphaFold is useful for understanding structure-functi...

BactInt: A domain driven transfer learning approach for extracting inter-bacterial associations from biomedical text.

Computational biology and chemistry
BACKGROUND: The healthy as well as dysbiotic state of an ecosystem like human body is known to be influenced not only by the presence of the bacterial groups in it, but also with respect to the associations within themselves. Evidence reported in bio...

Discovery of sparse, reliable omic biomarkers with Stabl.

Nature biotechnology
Adoption of high-content omic technologies in clinical studies, coupled with computational methods, has yielded an abundance of candidate biomarkers. However, translating such findings into bona fide clinical biomarkers remains challenging. To facili...

ML-FGAT: Identification of multi-label protein subcellular localization by interpretable graph attention networks and feature-generative adversarial networks.

Computers in biology and medicine
The prediction of multi-label protein subcellular localization (SCL) is a pivotal area in bioinformatics research. Recent advancements in protein structure research have facilitated the application of graph neural networks. This paper introduces a no...

Improving deep learning protein monomer and complex structure prediction using DeepMSA2 with huge metagenomics data.

Nature methods
Leveraging iterative alignment search through genomic and metagenome sequence databases, we report the DeepMSA2 pipeline for uniform protein single- and multichain multiple-sequence alignment (MSA) construction. Large-scale benchmarks show that DeepM...

iTTCA-MVL: A multi-view learning model based on physicochemical information and sequence statistical information for tumor T cell antigens identification.

Computers in biology and medicine
Immunotherapy is an emerging treatment method aimed at activating the human immune system and relying on its own immune function to kill cancer cells and tumor tissues. It has the advantages of wide applicability and minimal side effects. Effective i...

ProtEC: A Transformer Based Deep Learning System for Accurate Annotation of Enzyme Commission Numbers.

IEEE/ACM transactions on computational biology and bioinformatics
The advancements in next-generation sequencing technologies have given rise to large-scale, open-source protein databases consisting of hundreds of millions of sequences. However, to make these sequences useful in biomedical applications, they need t...