Bioinformatics and Machine Learning for Cancer Biology

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, a...

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Bibliographic Details
Format: eBook
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
Subjects:
Biology, life sciences
Research and information: general
Annexin family
architectural distortion
ARIMA
bidirectional long short-term memory neural network
biomarker
biomarker identification
biomedical informatics
bladder cancer
bladder urothelial carcinoma
breast cancer
cancer
CCLE
checkpoint
CPA4
ctDNA
deep learning
DEGs
depth-wise convolutional neural network
diagnosis
DNA damage repair genes
drug resistance
drug-drug interaction networks
estrogen receptor alpha
filtering
forecasting
Google Trends
image processing
immune cells
immunotherapy
incidence
liquid biopsy
machine learning
major histocompatibility complex
mammography
metastasis
modeling
molecular docking
mortality
multi-omics analysis
n/a
NGS
NNAR
ovarian cancer
papillary thyroid cancer (PTCa)
persistent organic pollutants
prediction
prognostic signature
proteomics
PUS7
R Shiny application
RMGs
RNA-seq
Romania
sitagliptin
survival analysis
T cell exhaustion
T-cell acute lymphoblastic leukemia
TBATS
therapeutic target
thyroid cancer (THCA)
thyroidectomy
transcriptomics
tumor mutational burden
VAF
variable selection
variant calling
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