Hypergeometric Similarity Measure for Spatial Analysis in Tissue Imaging Mass Spectrometry

Chanchala Kaddi; R. Mitchell Parry; May D. Wang; Mitchell Parry

doi:10.1109/BIBM.2011.113

Hypergeometric Similarity Measure for Spatial Analysis in Tissue Imaging Mass Spectrometry

Chanchala Kaddi
, R. Mitchell Parry
, May D. Wang
, Mitchell Parry

Appalachian State University

Georgia Institute of Technology

Research output: Contribution to journal › Article › peer-review

Original language	American English
Journal	Bioinformatics and Biomedicine
DOIs	https://doi.org/10.1109/BIBM.2011.113
State	Published - Nov 1 2011

Disciplines

Computer Sciences
Bioinformatics

Access to Document

10.1109/BIBM.2011.113License: Unspecified

Cite this

@article{1cb5084063e74c829f12e6a832a55d98,

title = "Hypergeometric Similarity Measure for Spatial Analysis in Tissue Imaging Mass Spectrometry",

author = "Chanchala Kaddi and Parry, \{R. Mitchell\} and Wang, \{May D.\} and Mitchell Parry",

note = "Tissue imaging mass spectrometry (TIMS) is a data-intensive technique for spatial biochemical analysis. TIMS contributes both molecular and spatial information to tissue analysis. We propose and evaluate a similarity measure, based on the hyper geometric distribution, for comparing m/z images from TIMS datasets, with the goal of identifying m/z values with similar spatial distributions.",

year = "2011",

month = nov,

day = "1",

doi = "10.1109/BIBM.2011.113",

language = "American English",

journal = "Bioinformatics and Biomedicine",

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T1 - Hypergeometric Similarity Measure for Spatial Analysis in Tissue Imaging Mass Spectrometry

AU - Kaddi, Chanchala

AU - Parry, R. Mitchell

AU - Wang, May D.

AU - Parry, Mitchell

N1 - Tissue imaging mass spectrometry (TIMS) is a data-intensive technique for spatial biochemical analysis. TIMS contributes both molecular and spatial information to tissue analysis. We propose and evaluate a similarity measure, based on the hyper geometric distribution, for comparing m/z images from TIMS datasets, with the goal of identifying m/z values with similar spatial distributions.

PY - 2011/11/1

Y1 - 2011/11/1

UR - http://doi.ieeecomputersociety.org/10.1109/BIBM.2011.113

U2 - 10.1109/BIBM.2011.113

DO - 10.1109/BIBM.2011.113

M3 - Article

JO - Bioinformatics and Biomedicine

JF - Bioinformatics and Biomedicine

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