Bioinformatics and Computational Biology in Human Diseases

Dear Colleagues,

Multi-omics, single-cell sequencing technologies, integrative biology, and precision medicine have all been promising approaches for the study of a wide range of human diseases. The big data era, with the rapid development of techniques such as next-generation sequencing, gene editing, cancer immunotherapy/CAR T cell therapy, and everything associated with COVID-19, also led to a huge challenge in data analysis, integration, and bioinformatics and computational models for the discovery of genes and signaling pathways that are essential for human diseases. Understanding the data from genomics, epigenetics, metabolisms, and proteomics, as well as the complex mechanisms in human diseases are the major challenges in current bioinformatics and computational biological studies.

In this Special Issue, we welcome contributions that integrate multi-omics, leverage single-cell sequencing technologies (e.g., scRNA-seq, scATAC-seq, and spatial transcriptomics), develop bioinformatics and computational models, and use machine learning/AI models, aiming at achieving a better understanding of human diseases. It is the aim of this Special Issue to provide a deeper comprehension of multi-omics, single-cell sequencing data, and the association between genetics and phenotypes, as well as biomarker discovery and patient stratification/clinical outcome prediction, that may ultimately lead to early diagnosis and precise and effective treatment.

Dr. Guangxu Jin
Guest Editor

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