PHI-DAC: Protein homology database through dihedral angle conservation

Noa Maatuk; Yitav Glantz-Gashai; Maya Rotman; Meirav Baydany; Gennadiy Fonar; Amir Shechvitz; Karin Shemer; Aviva Peleg; Eli Reuveni; Abraham O. Samson

doi:10.1093/bioinformatics/btu617

PHI-DAC: Protein homology database through dihedral angle conservation

Noa Maatuk, Yitav Glantz-Gashai, Maya Rotman, Meirav Baydany, Gennadiy Fonar, Amir Shechvitz, Karin Shemer, Aviva Peleg, Eli Reuveni, Abraham O. Samson

Bar-Ilan University

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

Abstract

Finding related conformations in the Protein Data Bank is essential in many areas of bioscience. To assist this task, we designed a dihedral angle database for searching protein segment homologs. The search engine relies on encoding of the protein coordinates into text characters representing amino acid sequence, ω and ψ dihedral angles. The search engine is advantageous owing to its high speed and interactive nature and is expected to assist scientists in discovering conformation homologs and evolutionary kinship.

Original language	English
Pages (from-to)	292-294
Number of pages	3
Journal	Bioinformatics
Volume	31
Issue number	2
DOIs	https://doi.org/10.1093/bioinformatics/btu617
State	Published - 15 Jan 2015

All Science Journal Classification (ASJC) codes

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/btu617

Cite this

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abstract = "Finding related conformations in the Protein Data Bank is essential in many areas of bioscience. To assist this task, we designed a dihedral angle database for searching protein segment homologs. The search engine relies on encoding of the protein coordinates into text characters representing amino acid sequence, ω and ψ dihedral angles. The search engine is advantageous owing to its high speed and interactive nature and is expected to assist scientists in discovering conformation homologs and evolutionary kinship.",

author = "Noa Maatuk and Yitav Glantz-Gashai and Maya Rotman and Meirav Baydany and Gennadiy Fonar and Amir Shechvitz and Karin Shemer and Aviva Peleg and Eli Reuveni and Samson, \{Abraham O.\}",

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doi = "10.1093/bioinformatics/btu617",

language = "الإنجليزيّة",

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T2 - Protein homology database through dihedral angle conservation

AU - Maatuk, Noa

AU - Glantz-Gashai, Yitav

AU - Rotman, Maya

AU - Baydany, Meirav

AU - Fonar, Gennadiy

AU - Shechvitz, Amir

AU - Shemer, Karin

AU - Peleg, Aviva

AU - Reuveni, Eli

AU - Samson, Abraham O.

PY - 2015/1/15

Y1 - 2015/1/15

N2 - Finding related conformations in the Protein Data Bank is essential in many areas of bioscience. To assist this task, we designed a dihedral angle database for searching protein segment homologs. The search engine relies on encoding of the protein coordinates into text characters representing amino acid sequence, ω and ψ dihedral angles. The search engine is advantageous owing to its high speed and interactive nature and is expected to assist scientists in discovering conformation homologs and evolutionary kinship.

AB - Finding related conformations in the Protein Data Bank is essential in many areas of bioscience. To assist this task, we designed a dihedral angle database for searching protein segment homologs. The search engine relies on encoding of the protein coordinates into text characters representing amino acid sequence, ω and ψ dihedral angles. The search engine is advantageous owing to its high speed and interactive nature and is expected to assist scientists in discovering conformation homologs and evolutionary kinship.

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DO - 10.1093/bioinformatics/btu617

M3 - مقالة

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SP - 292

EP - 294

JO - Bioinformatics

JF - Bioinformatics

IS - 2

ER -

PHI-DAC: Protein homology database through dihedral angle conservation

Abstract

All Science Journal Classification (ASJC) codes

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