A Novel Modeling in Mathematical Biology for Classification of Signal Peptides.

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Heterodimer Binding Scaffolds Recognition via the Analysis of Kinetically Hot Residues.iRNA-3typeA: Identifying Three Types of Modification at RNA's Adenosine Sites.Consistent prediction of GO protein localization.

P2860

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P2860

A Novel Modeling in Mathematical Biology for Classification of Signal Peptides.

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http://www.wikidata.org/entity/Q47559177

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2018 nî lūn-bûn

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2018年の論文

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2018年学术文章

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2018年学术文章

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2018年学术文章

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2018年学术文章

@zh-hans

2018年学术文章

@zh-my

2018年学术文章

@zh-sg

2018年學術文章

@yue

2018年學術文章

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name

A Novel Modeling in Mathematical Biology for Classification of Signal Peptides.

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A Novel Modeling in Mathematical Biology for Classification of Signal Peptides.

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Item

label

A Novel Modeling in Mathematical Biology for Classification of Signal Peptides.

@en

A Novel Modeling in Mathematical Biology for Classification of Signal Peptides.

@nl

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A Novel Modeling in Mathematical Biology for Classification of Signal Peptides.

@en

A Novel Modeling in Mathematical Biology for Classification of Signal Peptides.

@nl

P1476

A Novel Modeling in Mathematical Biology for Classification of Signal Peptides.

@en

P2093

Asma Ehsan

http://www.w3.org/2001/XMLSchema#string

Khalid Mahmood

http://www.w3.org/2001/XMLSchema#string

Sher Afzal Khan

http://www.w3.org/2001/XMLSchema#string

Yaser Daanial Khan

http://www.w3.org/2001/XMLSchema#string

P2860

Using neural networks for prediction of the subcellular location of proteins

Improved tools for biological sequence comparison.

Transfer of proteins across membranes. I. Presence of proteolytically processed and unprocessed nascent immunoglobulin light chains on membrane-bound ribosomes of murine myeloma

Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites

A new method for predicting signal sequence cleavage sites

The HMMTOP transmembrane topology prediction server

Signal peptidases

MultiLoc: prediction of protein subcellular localization using N-terminal targeting sequences, sequence motifs and amino acid composition

iSNO-PseAAC: predict cysteine S-nitrosylation sites in proteins by incorporating position specific amino acid propensity into pseudo amino acid composition

Prediction of protein antigenic determinants from amino acid sequences

P2888

s41598-018-19491-y

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scholarly article

P356

10.1038/S41598-018-19491-Y

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P407

English

P433

http://www.w3.org/2001/XMLSchema#string

P478

http://www.w3.org/2001/XMLSchema#string

P50

Kuo-Chen Chou

P577

2018-01-18T00:00:00Z

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P6179

1100351972

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A Novel Modeling in Mathematical Biology for Classification of Signal Peptides.

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P2860

P2860

A Novel Modeling in Mathematical Biology for Classification of Signal Peptides.

description

name

type

label

prefLabel

P1433

P1476

P2093

P2860

P2888

P304

P31

P356

P407

P433

P478

P50

P577

P6179

P698

P932

P356

P1433

P1476

P2093

P2860

P2888

P304

P31

P356

P407

P433

P478

P50

P577

P6179

P698

P932