Data
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Colon-cancer Kent Ridge - submitted by kidzik 1327 views, 1110 downloads, 0 comments
last edited by kidzik - Sep 2, 2011, 16:58 CET Rating
- Summary:
Contains 62 samples collected from colon-cancer patients.
- Data Shape: 2001 attributes, 62 instances (Integer,Floating Point,String)
- License: unknown (from UCI repository)
- Tags: cancer colon-cancer Regression
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: HDF5 (1.1 MB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
Contains 62 samples collected from colon-cancer patients.
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Lung Cancer (Michigan) - submitted by kidzik 1539 views, 1323 downloads, 0 comments
last edited by kidzik - Sep 14, 2011, 14:35 CET Rating
- Summary:
86 primary lung adenocarcinomas samples and 10 non-neoplastic lung samples are included. Each sample is described by 7129 genes.
- Data Shape: 7130 attributes, 96 instances (Integer,Floating Point,String)
- License: unknown (from UCI repository)
- Tags: cancer lung michigan tumor
- Tasks / Methods / Challenges: 1 tasks, 0 methods, 0 challenges
- Download: HDF5 (6.3 MB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
86 primary lung adenocarcinomas samples and 10 non-neoplastic lung samples are included. Each sample is described by 7129 genes.
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Lung cancer (Ontario) - submitted by kidzik 996 views, 1155 downloads, 0 comments
last edited by kidzik - Sep 14, 2011, 14:35 CET Rating
- Summary:
Gene expression data on tumor specimens from a total of 39 NSCLC samples.
- Data Shape: 2881 attributes, 39 instances (Integer,Floating Point,String)
- License: unknown (from UCI repository)
- Tags: cancer lung ontario
- Tasks / Methods / Challenges: 1 tasks, 0 methods, 0 challenges
- Download: HDF5 (1.1 MB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
Gene expression data on tumor specimens from a total of 39 NSCLC samples.
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Ovarian Cancer (NCI PBSII Data) - submitted by kidzik 687 views, 3117 downloads, 0 comments
last edited by kidzik - Sep 14, 2011, 14:35 CET Rating
- Summary:
Ovarian cancer due to family or personal history of cancer
- Data Shape: 15155 attributes, 253 instances (Integer,Floating Point,String)
- License: unknown (from UCI repository)
- Tags: cancer genetic history ovarian
- Tasks / Methods / Challenges: 1 tasks, 0 methods, 0 challenges
- Download: HDF5 (30.1 MB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
Ovarian cancer due to family or personal history of cancer
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Ovarian Cancer (NCI Q-Star Data) - submitted by kidzik 18 views, 247 downloads, 0 comments
last edited by kidzik - Sep 7, 2011, 12:21 CET Rating
- Summary:
The goal of this experiment is to identify proteomic patterns in serum that distinguish ovarian cancer from non-cancer.
- License: unknown (from UCI repository)
- Tags: cancer Classification nci ovarian qstar
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: arff (465.6 MB)
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
The goal of this experiment is to identify proteomic patterns in serum that distinguish ovarian cancer from non-cancer.
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Prostate Cancer - submitted by kidzik 15 views, 303 downloads, 0 comments
last edited by kidzik - Sep 5, 2011, 18:27 CET Rating
- Summary:
(A) Tumor versus Normal classification. (B) Prediction of clinical outcome
- License: unknown (from UCI repository)
- Tags: cancer Prediction prostate tumor
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: zip (4.8 MB)
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
(A) Tumor versus Normal classification. (B) Prediction of clinical outcome
Disclaimer
We are acting in good faith to make datasets submitted for the use of the scientific community available to everybody, but if you are a copyright holder and would like us to remove a dataset please inform us and we will do it as soon as possible.
Acknowledgements
This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
http://www.pascal-network.org/.