Prediction of human protein function according to Gene Ontology categories

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Prediction of human protein function according to Gene Ontology categories. / Jensen, L J; Gupta, Ramneek; Staerfeldt, H-H; Brunak, S.

In: Bioinformatics, Vol. 19, No. 5, 2003, p. 635-42.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Jensen, LJ, Gupta, R, Staerfeldt, H-H & Brunak, S 2003, 'Prediction of human protein function according to Gene Ontology categories', Bioinformatics, vol. 19, no. 5, pp. 635-42.

APA

Jensen, L. J., Gupta, R., Staerfeldt, H-H., & Brunak, S. (2003). Prediction of human protein function according to Gene Ontology categories. Bioinformatics, 19(5), 635-42.

Vancouver

Jensen LJ, Gupta R, Staerfeldt H-H, Brunak S. Prediction of human protein function according to Gene Ontology categories. Bioinformatics. 2003;19(5):635-42.

Author

Jensen, L J ; Gupta, Ramneek ; Staerfeldt, H-H ; Brunak, S. / Prediction of human protein function according to Gene Ontology categories. In: Bioinformatics. 2003 ; Vol. 19, No. 5. pp. 635-42.

Bibtex

@article{c814cc72aceb4adc860b7ec7b3fb8a1d,
title = "Prediction of human protein function according to Gene Ontology categories",
abstract = "MOTIVATION: The human genome project has led to the discovery of many human protein coding genes which were previously unknown. As a large fraction of these are functionally uncharacterized, it is of interest to develop methods for predicting their molecular function from sequence. RESULTS: We have developed a method for prediction of protein function for a subset of classes from the Gene Ontology classification scheme. This subset includes several pharmaceutically interesting categories-transcription factors, receptors, ion channels, stress and immune response proteins, hormones and growth factors can all be predicted. Although the method relies on protein sequences as the sole input, it does not rely on sequence similarity, but instead on sequence derived protein features such as predicted post translational modifications (PTMs), protein sorting signals and physical/chemical properties calculated from the amino acid composition. This allows for prediction of the function for orphan proteins where no homologs can be found. Using this method we propose two novel receptors in the human genome, and further demonstrate chromosomal clustering of related proteins.",
author = "Jensen, {L J} and Ramneek Gupta and H-H Staerfeldt and S Brunak",
year = "2003",
language = "English",
volume = "19",
pages = "635--42",
journal = "Computer Applications in the Biosciences",
issn = "1471-2105",
publisher = "Oxford University Press",
number = "5",

}

RIS

TY - JOUR

T1 - Prediction of human protein function according to Gene Ontology categories

AU - Jensen, L J

AU - Gupta, Ramneek

AU - Staerfeldt, H-H

AU - Brunak, S

PY - 2003

Y1 - 2003

N2 - MOTIVATION: The human genome project has led to the discovery of many human protein coding genes which were previously unknown. As a large fraction of these are functionally uncharacterized, it is of interest to develop methods for predicting their molecular function from sequence. RESULTS: We have developed a method for prediction of protein function for a subset of classes from the Gene Ontology classification scheme. This subset includes several pharmaceutically interesting categories-transcription factors, receptors, ion channels, stress and immune response proteins, hormones and growth factors can all be predicted. Although the method relies on protein sequences as the sole input, it does not rely on sequence similarity, but instead on sequence derived protein features such as predicted post translational modifications (PTMs), protein sorting signals and physical/chemical properties calculated from the amino acid composition. This allows for prediction of the function for orphan proteins where no homologs can be found. Using this method we propose two novel receptors in the human genome, and further demonstrate chromosomal clustering of related proteins.

AB - MOTIVATION: The human genome project has led to the discovery of many human protein coding genes which were previously unknown. As a large fraction of these are functionally uncharacterized, it is of interest to develop methods for predicting their molecular function from sequence. RESULTS: We have developed a method for prediction of protein function for a subset of classes from the Gene Ontology classification scheme. This subset includes several pharmaceutically interesting categories-transcription factors, receptors, ion channels, stress and immune response proteins, hormones and growth factors can all be predicted. Although the method relies on protein sequences as the sole input, it does not rely on sequence similarity, but instead on sequence derived protein features such as predicted post translational modifications (PTMs), protein sorting signals and physical/chemical properties calculated from the amino acid composition. This allows for prediction of the function for orphan proteins where no homologs can be found. Using this method we propose two novel receptors in the human genome, and further demonstrate chromosomal clustering of related proteins.

M3 - Journal article

C2 - 12651722

VL - 19

SP - 635

EP - 642

JO - Computer Applications in the Biosciences

JF - Computer Applications in the Biosciences

SN - 1471-2105

IS - 5

ER -

ID: 40749783