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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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Format: Online
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects:
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
Online Access:ONIX_20230220_9783036548142_17
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