New Results
Prediction of best features in heterogeneous Lung adenocarcinoma samples using Least Absolute Shrinking and Selection Operator
View ORCID ProfileAteeq Muhammed Khaliq, RG Sharathchandra, View ORCID ProfileMeenakshi Rajamohan
doi: https://doi.org/10.1101/765792
Ateeq Muhammed Khaliq
Tumkur University
RG Sharathchandra
Tumkur University
Meenakshi Rajamohan
Tumkur University
Posted September 11, 2019.
Prediction of best features in heterogeneous Lung adenocarcinoma samples using Least Absolute Shrinking and Selection Operator
Ateeq Muhammed Khaliq, RG Sharathchandra, Meenakshi Rajamohan
bioRxiv 765792; doi: https://doi.org/10.1101/765792
Subject Area
Subject Areas
- Biochemistry (11573)
- Bioengineering (8623)
- Bioinformatics (28874)
- Biophysics (14805)
- Cancer Biology (11944)
- Cell Biology (17170)
- Clinical Trials (138)
- Developmental Biology (9306)
- Ecology (14022)
- Epidemiology (2067)
- Evolutionary Biology (18129)
- Genetics (12148)
- Genomics (16619)
- Immunology (11709)
- Microbiology (27697)
- Molecular Biology (11392)
- Neuroscience (60106)
- Paleontology (447)
- Pathology (1849)
- Pharmacology and Toxicology (3184)
- Physiology (4878)
- Plant Biology (10279)
- Synthetic Biology (2849)
- Systems Biology (7291)
- Zoology (1619)