An evolutionary conservation & rigidity analysis machine learning approach for detecting critical protein residues

Filip Jagodzinski; Bahar Akbal-Delibas; Nurit Haspel

doi:10.1145/2506583.2506708

An evolutionary conservation & rigidity analysis machine learning approach for detecting critical protein residues

Filip Jagodzinski
, Bahar Akbal-Delibas
, Nurit Haspel

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013
Pages	779-785
Number of pages	7
DOIs	https://doi.org/10.1145/2506583.2506708
State	Published - 2013
Event	2013 4th ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013 - Wshington, DC, United States Duration: Sep 22 2013 → Sep 25 2013

Publication series

Name	2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013

Conference

Conference	2013 4th ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013
Country/Territory	United States
City	Wshington, DC
Period	9/22/13 → 9/25/13

ASJC Scopus Subject Areas

Bioengineering
Biomedical Engineering
Health Informatics

Keywords

Conservation
Critical residues
Machine learning
Rigidity

Access to Document

10.1145/2506583.2506708

Cite this

Jagodzinski, F., Akbal-Delibas, B., & Haspel, N. (2013). An evolutionary conservation & rigidity analysis machine learning approach for detecting critical protein residues. In 2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013 (pp. 779-785). (2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013). https://doi.org/10.1145/2506583.2506708

An evolutionary conservation & rigidity analysis machine learning approach for detecting critical protein residues. / Jagodzinski, Filip; Akbal-Delibas, Bahar; Haspel, Nurit.
2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013. 2013. p. 779-785 (2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Jagodzinski, F, Akbal-Delibas, B & Haspel, N 2013, An evolutionary conservation & rigidity analysis machine learning approach for detecting critical protein residues. in 2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013. 2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013, pp. 779-785, 2013 4th ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013, Wshington, DC, United States, 9/22/13. https://doi.org/10.1145/2506583.2506708

Jagodzinski F, Akbal-Delibas B, Haspel N. An evolutionary conservation & rigidity analysis machine learning approach for detecting critical protein residues. In 2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013. 2013. p. 779-785. (2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013). doi: 10.1145/2506583.2506708

Jagodzinski, Filip ; Akbal-Delibas, Bahar ; Haspel, Nurit. / An evolutionary conservation & rigidity analysis machine learning approach for detecting critical protein residues. 2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013. 2013. pp. 779-785 (2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013).

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AU - Jagodzinski, Filip

AU - Akbal-Delibas, Bahar

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KW - Critical residues

KW - Machine learning

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BT - 2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013

T2 - 2013 4th ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013

Y2 - 22 September 2013 through 25 September 2013

ER -

An evolutionary conservation & rigidity analysis machine learning approach for detecting critical protein residues

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

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