svm models specific to lung cancer cell lines (Broad Institute Inc)
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Broad Institute Inc
svm models specific to lung cancer cell lines
Svm Models Specific To Lung Cancer Cell Lines, supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/svm+models+specific+to+lung+cancer+cell+lines/svm+models+specific+to+lung+cancer+cell+lines/pmc05528934-445-6-27
Average 90 stars, based on 1 article reviews
Svm Models Specific To Lung Cancer Cell Lines, supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/svm+models+specific+to+lung+cancer+cell+lines/svm+models+specific+to+lung+cancer+cell+lines/pmc05528934-445-6-27
Average 90 stars, based on 1 article reviews
svm models specific to lung cancer cell lines - by Bioz Stars,
2026-11
90/100 stars
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Expressing:Article Title: Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning Article Snippet: To mitigate tissue‐specific effects, we rederived SVM models specific to lung cancer (lung) and hematopoietic and lymphoid tissue cancer (hematopoietic) cell lines using expression data from the broad institute ( www.broadinstitute.org/ccle/home ; “CCLE_Expression_2012‐09‐29.res” and “CCLE_NP24.2009_profiling_2012.02.20.csv”). Gene Expression:Article Title: Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning Article Snippet: To mitigate tissue‐specific effects, we rederived SVM models specific to lung cancer (lung) and hematopoietic and lymphoid tissue cancer (hematopoietic) cell lines using expression data from the broad institute ( www.broadinstitute.org/ccle/home ; “CCLE_Expression_2012‐09‐29.res” and “CCLE_NP24.2009_profiling_2012.02.20.csv”). Derivative Assay:Article Title: Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning Article Snippet: To mitigate tissue‐specific effects, we rederived SVM models specific to lung cancer (lung) and hematopoietic and lymphoid tissue cancer (hematopoietic) cell lines using expression data from the broad institute ( www.broadinstitute.org/ccle/home ; “CCLE_Expression_2012‐09‐29.res” and “CCLE_NP24.2009_profiling_2012.02.20.csv”). Mutagenesis:Article Title: Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning Article Snippet: To mitigate tissue‐specific effects, we rederived SVM models specific to lung cancer (lung) and hematopoietic and lymphoid tissue cancer (hematopoietic) cell lines using expression data from the broad institute ( www.broadinstitute.org/ccle/home ; “CCLE_Expression_2012‐09‐29.res” and “CCLE_NP24.2009_profiling_2012.02.20.csv”). Labeling:Article Title: Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning Article Snippet: To mitigate tissue‐specific effects, we rederived SVM models specific to lung cancer (lung) and hematopoietic and lymphoid tissue cancer (hematopoietic) cell lines using expression data from the broad institute ( www.broadinstitute.org/ccle/home ; “CCLE_Expression_2012‐09‐29.res” and “CCLE_NP24.2009_profiling_2012.02.20.csv”). Construct:Article Title: Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning Article Snippet: To mitigate tissue‐specific effects, we rederived SVM models specific to lung cancer (lung) and hematopoietic and lymphoid tissue cancer (hematopoietic) cell lines using expression data from the broad institute ( www.broadinstitute.org/ccle/home ; “CCLE_Expression_2012‐09‐29.res” and “CCLE_NP24.2009_profiling_2012.02.20.csv”). |