AIMC Topic: Disease Susceptibility

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Systems Human Immunology and AI: Immune Setpoint and Immune Health.

Annual review of immunology
The immune system, critical for human health and implicated in many diseases, defends against pathogens, monitors physiological stress, and maintains tissue and organismal homeostasis. It exhibits substantial variability both within and across indivi...

Biomarker Identification for Preterm Birth Susceptibility: Vaginal Microbiome Meta-Analysis Using Systems Biology and Machine Learning Approaches.

American journal of reproductive immunology (New York, N.Y. : 1989)
PROBLEM: The vaginal microbiome has a substantial role in the occurrence of preterm birth (PTB), which contributes substantially to neonatal mortality worldwide. However, current bioinformatics approaches mostly concentrate on the taxonomic classific...

CellGO: a novel deep learning-based framework and webserver for cell-type-specific gene function interpretation.

Briefings in bioinformatics
Interpreting the function of genes and gene sets identified from omics experiments remains a challenge, as current pathway analysis tools often fail to consider the critical biological context, such as tissue or cell-type specificity. To address this...

The accurate prediction and characterization of cancerlectin by a combined machine learning and GO analysis.

Briefings in bioinformatics
Cancerlectins, lectins linked to tumor progression, have become the focus of cancer therapy research for their carbohydrate-binding specificity. However, the specific characterization for cancerlectins involved in tumor progression is still unclear. ...

Multi-view Multichannel Attention Graph Convolutional Network for miRNA-disease association prediction.

Briefings in bioinformatics
MOTIVATION: In recent years, a growing number of studies have proved that microRNAs (miRNAs) play significant roles in the development of human complex diseases. Discovering the associations between miRNAs and diseases has become an important part of...

Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression.

JAMA psychiatry
IMPORTANCE: Diverse models have been developed to predict psychosis in patients with clinical high-risk (CHR) states. Whether prediction can be improved by efficiently combining clinical and biological models and by broadening the risk spectrum to yo...

Distinct Transcriptional and Anti-Mycobacterial Profiles of Peripheral Blood Monocytes Dependent on the Ratio of Monocytes: Lymphocytes.

EBioMedicine
The ratio of monocytes and lymphocytes (ML ratio) in peripheral blood is associated with tuberculosis and malaria disease risk and cancer and cardiovascular disease outcomes. We studied anti-mycobacterial function and the transcriptome of monocytes i...