Biomarker clustering of colorectal cancer data to complement clinical classification

In this paper, we describe a dataset relating to cellular and physical conditions of patients who are operated upon to remove colorectal tumours. This data provides a unique insight into immunological status at the point of tumour removal, tumour classification and postoperative survival. Attemp...

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Main Authors: Roadknight, Chris, Aickelin, Uwe, Ladas, Alex, Soria, Daniele, Scholefield, John, Durrant, Lindy
Format: Conference or Workshop Item
Published: 2012
Online Access:https://eprints.nottingham.ac.uk/2035/
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author Roadknight, Chris
Aickelin, Uwe
Ladas, Alex
Soria, Daniele
Scholefield, John
Durrant, Lindy
author_facet Roadknight, Chris
Aickelin, Uwe
Ladas, Alex
Soria, Daniele
Scholefield, John
Durrant, Lindy
author_sort Roadknight, Chris
building Nottingham Research Data Repository
collection Online Access
description In this paper, we describe a dataset relating to cellular and physical conditions of patients who are operated upon to remove colorectal tumours. This data provides a unique insight into immunological status at the point of tumour removal, tumour classification and postoperative survival. Attempts are made to cluster this dataset and important subsets of it in an effort to characterize the data and validate existing standards for tumour classification. It is apparent from optimal clustering that existing tumour classification is largely unrelated to immunological factors within a patient and that there may be scope for re-evaluating treatment options and survival estimates based on a combination of tumour physiology and patient histochemistry.
first_indexed 2025-11-14T18:16:56Z
format Conference or Workshop Item
id nottingham-2035
institution University of Nottingham Malaysia Campus
institution_category Local University
last_indexed 2025-11-14T18:16:56Z
publishDate 2012
recordtype eprints
repository_type Digital Repository
spelling nottingham-20352020-05-04T20:22:48Z https://eprints.nottingham.ac.uk/2035/ Biomarker clustering of colorectal cancer data to complement clinical classification Roadknight, Chris Aickelin, Uwe Ladas, Alex Soria, Daniele Scholefield, John Durrant, Lindy In this paper, we describe a dataset relating to cellular and physical conditions of patients who are operated upon to remove colorectal tumours. This data provides a unique insight into immunological status at the point of tumour removal, tumour classification and postoperative survival. Attempts are made to cluster this dataset and important subsets of it in an effort to characterize the data and validate existing standards for tumour classification. It is apparent from optimal clustering that existing tumour classification is largely unrelated to immunological factors within a patient and that there may be scope for re-evaluating treatment options and survival estimates based on a combination of tumour physiology and patient histochemistry. 2012 Conference or Workshop Item PeerReviewed Roadknight, Chris, Aickelin, Uwe, Ladas, Alex, Soria, Daniele, Scholefield, John and Durrant, Lindy (2012) Biomarker clustering of colorectal cancer data to complement clinical classification. In: Federated Conference on Computer Science and Information Systems (FedCSIS), 9-12 Sept 2012, Wrocław, Poland. (Unpublished)
spellingShingle Roadknight, Chris
Aickelin, Uwe
Ladas, Alex
Soria, Daniele
Scholefield, John
Durrant, Lindy
Biomarker clustering of colorectal cancer data to complement clinical classification
title Biomarker clustering of colorectal cancer data to complement clinical classification
title_full Biomarker clustering of colorectal cancer data to complement clinical classification
title_fullStr Biomarker clustering of colorectal cancer data to complement clinical classification
title_full_unstemmed Biomarker clustering of colorectal cancer data to complement clinical classification
title_short Biomarker clustering of colorectal cancer data to complement clinical classification
title_sort biomarker clustering of colorectal cancer data to complement clinical classification
url https://eprints.nottingham.ac.uk/2035/