Bioinformatics of Autoimmune Diseases (Chapman & Hall/crc Computational Biology Series)

191.82 SGD
会員価格
172.64
English

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Product Description

Autoimmune diseases arise when the immune system misidentifies the body’s own tissues as threats, a catastrophic failure of self-recognition that leads to chronic inflammation, tissue damage, and long-term disability. Bioinformatics of Autoimmune Diseases is a timely and comprehensive guide that explores not only the immunological basis of these disorders but also the cutting-edge bioinformatics approaches used to analyze the genomic, transcriptomic, and epigenomic data driving modern discovery. Structured to bridge foundational immunology with advanced computational analysis, this book offers readers a progression from the molecular mechanisms of immune function and dysfunction to the bioinformatics pipelines used to investigate them. Early chapters provide a thorough grounding in immune cell biology, immune checkpoints, and disease pathogenesis. Subsequent chapters guide readers through practical analyses of autoimmune disease data, covering RNA-Seq, variant analysis, microbiome profiling, ATAC-Seq, ChIP-Seq, single-cell sequencing, and gene therapy and autoimmune diseases. Bioinformatics tools are introduced using Python with step-by-step workflows, enabling hands-on engagement with real datasets. Written by a professor of bioinformatics and developer of bioinformatics tools, the book draws from over a decade of broad experience in computational biology. With detailed illustrations, curated datasets, and a clear emphasis on reproducibility, it serves as a foundational resource for graduate students, clinicians, biomedical researchers, and anyone seeking to decode the bioinformatics foundations and mechanisms driving autoimmune disease.

Bioinformatics of Autoimmune Diseases is a timely and comprehensive guide that explores not only the immunological basis of these disorders but also the cutting-edge bioinformatics approaches used to analyze the genomic, transcriptomic, and epigenomic data driving modern discovery.

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