Artículos en revistas:
Pretata: predicting TATA binding proteins with novel features and dimensionality reduction strategy
Pretata: predicting TATA binding proteins with novel features and dimensionality reduction strategy
Año:2016
Áreas de investigación
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Biología molecular, celular y genética, -
Ciencias de la computación y tecnología informática
Datos
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Descripción
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| It is necessary and essential to discovery protein function from the novel primary sequences. Wet lab experimental procedures are not only time-consuming, but also costly, so predicting protein structure and function reliably based only on amino acid sequence has significant value. TATA-binding protein (TBP) is a kind of DNA binding protein, which plays a key role in the transcription regulation. Our study proposed an automatic approach for identifying TATA-binding proteins efficiently, accurately, and conveniently. This method would guide for the special protein identification with computational intelligence strategies. | |
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Internacional
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Si |
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JCR del ISI
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Si |
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Título de la revista
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Bmc Systems Biology |
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ISSN
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1752-0509 |
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Factor de impacto JCR
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2,208 |
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Información de impacto
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Volumen
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DOI
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Número de revista
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Desde la página
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401 |
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Hasta la página
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412 |
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Mes
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DICIEMBRE |
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Ranking
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Participantes
- Autor: Quan Zou
- Autor: Shixiang Wan
- Autor: Ying Ju
- Autor: Jijun Tang
- Autor: Xiangxiang Zeng . (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
- Creador: Grupo de Investigación: Grupo de Inteligencia Artificial (LIA)
S2i 2023 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)