Accurate sequence-based prediction of catalytic residues (Q48325580)

10 February 2018

title

Accurate sequence-based prediction of catalytic residues (English)

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10 February 2018

author

Lukasz Kurgan

6

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author name string

Tuo Zhang

1

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Hua Zhang

2

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Ke Chen

3

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Shiyi Shen

4

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Jishou Ruan

5

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language of work or name

English

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publication date

18 August 2008

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published in

Bioinformatics

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volume

24

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issue

20

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page(s)

2329-2338

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Gapped BLAST and PSI-BLAST: a new generation of protein database search programs

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How accurate and statistically robust are catalytic site predictions based on closeness centrality?

21 January 2018

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Using a neural network and spatial clustering to predict the location of active sites in enzymes

21 January 2018

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21 January 2018

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Analysis of an optimal hidden Markov model for secondary structure prediction

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Comparison of site-specific rate-inference methods for protein sequences: empirical Bayesian methods are superior

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Prediction of catalytic residues in enzymes based on known tertiary structure, stability profile, and sequence conservation

21 January 2018

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Prediction of catalytic residues using Support Vector Machine with selected protein sequence and structural properties

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Predicting and annotating catalytic residues: an information theoretic approach

21 January 2018

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Correlation of sequence hydrophobicities measures similarity in three-dimensional protein structure

21 January 2018

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Using a library of structural templates to recognise catalytic sites and explore their evolution in homologous families

21 January 2018

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21 January 2018

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21 January 2018

Identifiers

DOI

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10 February 2018

journals/bioinformatics/ZhangZCSRK08

DBLP publication ID

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DBLP Dataset 2021-01-02

28 January 2021

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10 February 2018