(Q48523184)

12 February 2018

title

A simple and fast secondary structure prediction method using hidden neural networks. (English)

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12 February 2018

4

Jaap Heringa

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12 February 2018

author name string

Kuang Lin

series ordinal

1

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12 February 2018

Victor A Simossis

series ordinal

2

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12 February 2018

Willam R Taylor

series ordinal

3

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12 February 2018

language of work or name

English

0 references

publication date

17 September 2004

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12 February 2018

number of pages

8

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based on heuristic

inferred from page(s)

published in

Bioinformatics

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12 February 2018

volume

21

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12 February 2018

page(s)

152-159

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12 February 2018

issue

2

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12 February 2018

Simple consensus procedures are effective and sufficient in secondary structure prediction.

cites work

1 reference

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21 January 2018

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Global properties of the mapping between local amino acid sequence and local structure in proteins

21 January 2018

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21 January 2018

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21 January 2018

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Protein secondary structure prediction based on position-specific scoring matrices

21 January 2018

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21 January 2018

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Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features

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Hidden Markov models that use predicted local structure for fold recognition: alphabets of backbone geometry

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21 January 2018

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21 January 2018

Hidden neural networks.

1 reference

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21 January 2018

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21 January 2018

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21 January 2018

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21 January 2018

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21 January 2018

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21 January 2018

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Prediction of protein secondary structure at better than 70% accuracy

21 January 2018

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Capping and alpha-helix stability

21 January 2018

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Interactions of HIV-1 proteins gp120 and Nef with cellular partners define a novel allosteric paradigm

21 January 2018

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A modified definition of Sov, a segment-based measure for protein secondary structure prediction assessment.

21 January 2018

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Benchmarking secondary structure prediction for fold recognition

21 January 2018

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10.1093/BIOINFORMATICS/BTH487

21 January 2018

Identifiers

DOI

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12 February 2018

journals/bioinformatics/LinSTH05

DBLP publication ID

1 reference

DBLP Dataset 2021-01-02

28 January 2021

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12 February 2018