Identification of core T cell network based on immunome interactome.

Gabriel Teku; Csaba Ortutay; Mauno Vihinen

doi:10.1186/1752-0509-8-17

Identification of core T cell network based on immunome interactome.

Gabriel Teku, Csaba Ortutay, Mauno Vihinen

Proteinbioinformatik

Forskningsoutput: Tidskriftsbidrag › Artikel i vetenskaplig tidskrift › Peer review

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Sammanfattning

Data-driven studies on the dynamics of reconstructed protein-protein interaction (PPI) networks facilitate investigation and identification of proteins important for particular processes or diseases and reduces time and costs of experimental verification. Modeling the dynamics of very large PPI networks is computationally costly.

Originalspråk	engelska
Artikelnummer	17
Tidskrift	BMC Systems Biology
Volym	8
Nummer	1
DOI	https://doi.org/10.1186/1752-0509-8-17
Status	Published - 2014

Ämnesklassifikation (UKÄ)

Bioinformatik och beräkningsbiologi

Tillgång till dokument

10.1186/1752-0509-8-17

BMC_Teku_et_al

http://www.ncbi.nlm.nih.gov/pubmed/24528953?dopt=Abstract

1 Doktorsavhandling (sammanläggning)

Computational analysis on the effects of variations in T and B cells. Primary immunodeficiencies and cancer neoepitopes
Teku, G. N., 2017, Lund: Lund University: Faculty of Medicine. 74 s.
Forskningsoutput: Avhandling › Doktorsavhandling (sammanläggning)

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title = "Identification of core T cell network based on immunome interactome.",

abstract = "Data-driven studies on the dynamics of reconstructed protein-protein interaction (PPI) networks facilitate investigation and identification of proteins important for particular processes or diseases and reduces time and costs of experimental verification. Modeling the dynamics of very large PPI networks is computationally costly.",

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DO - 10.1186/1752-0509-8-17

M3 - Article

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JO - BMC Systems Biology

JF - BMC Systems Biology

IS - 1

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ER -

Identification of core T cell network based on immunome interactome.

Sammanfattning

Ämnesklassifikation (UKÄ)

Tillgång till dokument

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Forskningsoutput

Computational analysis on the effects of variations in T and B cells. Primary immunodeficiencies and cancer neoepitopes

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