Analysis of protein profiles using fuzzy clustering methods: case of malignant and normal cervical tissues

Gopal Raghunath Karemore; Sujatha Ukendt; Lavanya Rai; V.B Kartha; Santhosh C

Analysis of protein profiles using fuzzy clustering methods: case of malignant and normal cervical tissues

Gopal Raghunath Karemore, Sujatha Ukendt, Lavanya Rai, V.B Kartha, Santhosh C

Datalogisk Institut

Abstract

The tissue protein profiles of healthy volunteers and volunteers with cervical cancer were

recorded using High Performance Liquid Chromatography combined with Laser Induced

Fluorescence technique (HPLC-LIF) developed in our lab. We analyzed the protein

profile data using different clustering methods for their classification followed by various

validation measures. The clustering algorithms used for the study were K- means, K-

medoid, Fuzzy C-means, Gustafson-Kessel, and Gath-Geva. The results presented in this

study conclude that the protein profiles of tissue samples recorded by using the HPLC-

LIF system and the data analyzed by clustering algorithms quite successfully classifies

them as belonging from normal and malignant conditions.

Originalsprog	Engelsk
Publikationsdato	2008
Antal sider	1
Status	Udgivet - 2008
Begivenhed	The 27 Annual Convention of the IACR Networking Research to Applications & International Symposium on Frontiers in Functional Genomics - Ahmadabad, Indien Varighed: 7 feb. 2008 → 9 feb. 2008 Konferencens nummer: 27

Konference

Konference	The 27 Annual Convention of the IACR Networking Research to Applications & International Symposium on Frontiers in Functional Genomics
Nummer	27
Land/Område	Indien
By	Ahmadabad
Periode	07/02/2008 → 09/02/2008

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Analysis of protein profiles using fuzzy clustering methods: case of malignant and normal cervical tissues . / Karemore, Gopal Raghunath; Ukendt, Sujatha; Rai, Lavanya et al.
2008. Poster session præsenteret på The 27 Annual Convention of the IACR Networking Research to Applications & International Symposium on Frontiers in Functional Genomics, Ahmadabad, Indien.

Publikation: Konferencebidrag › Poster › Forskning

@conference{bfa61c10e18411ddb5fc000ea68e967b,

title = "Analysis of protein profiles using fuzzy clustering methods: case of malignant and normal cervical tissues ",

abstract = "The tissue protein profiles of healthy volunteers and volunteers with cervical cancer wererecorded using High Performance Liquid Chromatography combined with Laser InducedFluorescence technique (HPLC-LIF) developed in our lab. We analyzed the proteinprofile data using different clustering methods for their classification followed by variousvalidation measures. The clustering algorithms used for the study were K- means, K-medoid, Fuzzy C-means, Gustafson-Kessel, and Gath-Geva. The results presented in thisstudy conclude that the protein profiles of tissue samples recorded by using the HPLC-LIF system and the data analyzed by clustering algorithms quite successfully classifiesthem as belonging from normal and malignant conditions.",

author = "Karemore, {Gopal Raghunath} and Sujatha Ukendt and Lavanya Rai and V.B Kartha and Santhosh C",

year = "2008",

language = "English",

note = "The 27 Annual Convention of the IACR Networking Research to Applications & International Symposium on Frontiers in Functional Genomics ; Conference date: 07-02-2008 Through 09-02-2008",

}

TY - CONF

T1 - Analysis of protein profiles using fuzzy clustering methods

T2 - The 27 Annual Convention of the IACR Networking Research to Applications & International Symposium on Frontiers in Functional Genomics

AU - Karemore, Gopal Raghunath

AU - Ukendt, Sujatha

AU - Rai, Lavanya

AU - Kartha, V.B

AU - C, Santhosh

N1 - Conference code: 27

PY - 2008

Y1 - 2008

N2 - The tissue protein profiles of healthy volunteers and volunteers with cervical cancer wererecorded using High Performance Liquid Chromatography combined with Laser InducedFluorescence technique (HPLC-LIF) developed in our lab. We analyzed the proteinprofile data using different clustering methods for their classification followed by variousvalidation measures. The clustering algorithms used for the study were K- means, K-medoid, Fuzzy C-means, Gustafson-Kessel, and Gath-Geva. The results presented in thisstudy conclude that the protein profiles of tissue samples recorded by using the HPLC-LIF system and the data analyzed by clustering algorithms quite successfully classifiesthem as belonging from normal and malignant conditions.

AB - The tissue protein profiles of healthy volunteers and volunteers with cervical cancer wererecorded using High Performance Liquid Chromatography combined with Laser InducedFluorescence technique (HPLC-LIF) developed in our lab. We analyzed the proteinprofile data using different clustering methods for their classification followed by variousvalidation measures. The clustering algorithms used for the study were K- means, K-medoid, Fuzzy C-means, Gustafson-Kessel, and Gath-Geva. The results presented in thisstudy conclude that the protein profiles of tissue samples recorded by using the HPLC-LIF system and the data analyzed by clustering algorithms quite successfully classifiesthem as belonging from normal and malignant conditions.

M3 - Poster

Y2 - 7 February 2008 through 9 February 2008

ER -

Analysis of protein profiles using fuzzy clustering methods: case of malignant and normal cervical tissues

Abstract

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