Bioinformatics and Machine Learning for Cancer Biology

Cancer is a leading cause of death worldwide, claiming millions of lives each year. Cancer biology is an essential research field to understand how cancer develops, evolves, and responds to therapy. By taking advantage of a series of “omics” technologies (e.g., genomics, transcriptomics, and epigeno...

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フォーマット:	Online
言語:	英語
出版事項:	MDPI - Multidisciplinary Digital Publishing Institute 2023
主題:	tumor mutational burden DNA damage repair genes immunotherapy biomarker biomedical informatics breast cancer estrogen receptor alpha persistent organic pollutants drug-drug interaction networks molecular docking NGS ctDNA VAF liquid biopsy filtering variant calling DEGs diagnosis ovarian cancer PUS7 RMGs CPA4 bladder urothelial carcinoma immune cells T cell exhaustion checkpoint architectural distortion image processing depth-wise convolutional neural network mammography bladder cancer Annexin family survival analysis prognostic signature therapeutic target R Shiny application RNA-seq proteomics multi-omics analysis T-cell acute lymphoblastic leukemia CCLE sitagliptin thyroid cancer (THCA) papillary thyroid cancer (PTCa) thyroidectomy metastasis drug resistance n/a biomarker identification transcriptomics machine learning prediction variable selection major histocompatibility complex bidirectional long short-term memory neural network deep learning cancer incidence mortality modeling forecasting Google Trends Romania ARIMA TBATS NNAR thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
オンライン･アクセス:	ONIX_20230220_9783036548142_17
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ONIX_20230220_9783036548142_17

Bioinformatics and Machine Learning for Cancer Biology

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