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1.
Military Medical Sciences ; (12): 6-11, 2015.
Artículo en Chino | WPRIM (Pacífico Occidental) | ID: wpr-461844

RESUMEN

Objective To study the interaction between human microRNA ( miRNA) and 5′trailer regions of Ebola virus genome from the perspective of bioinformatics so as to facilitate prevention and treatment of Ebola virus .Method The miRNA target prediction software Pita and RNAhybrid were used to predict the human miRNAs which could bind the 5′trailer regions of Ebola virus genomes before the miRNAs were annotated by g:Profiler web server .Results and Conclusion There may be complex interactions between human miRNAs and the 5′trailer regions of Ebola virus .Previous reports about the interaction between host miRNA and 5′trailer region of virus genome suggest that the interaction between human miRNA and 5′trailer region of Ebola virus may have effect on replication of Ebola virus and human cells .This work may provide new ideas on prevention and treatment of Ebola virus .

2.
Military Medical Sciences ; (12): 612-616, 2014.
Artículo en Chino | WPRIM (Pacífico Occidental) | ID: wpr-473987

RESUMEN

Objective To conduct a pilot study on genome-wide in vivo protein-RNA interactions in E.coli.Methods Bacterial lysate was treated with RNase before the RNA fragments protected by proteins were extracted from treated lysate and used to construct cDNA library that was applied to high-throughput sequencing .Finally, the transcripts bound by proteins were obtained by bioinformatics analysis .Results A total of 3193 transcripts were obtained , including 2234 mRNAs, 47 sRNAs, 39 tRNAs, 11 rRNAs, and 862 intergenic regions .Conclusion Some information of transcripts interacting with proteins in E.coli is acquired , which will facilitate further studies of protein-RNA interactions .

3.
Bioinformatics ; 18(2): 325-6, 2002 Feb.
Artículo en Inglés | MEDLINE | ID: mdl-11847083

RESUMEN

A method that incorporates feature selection into Fisher's linear discriminant analysis for gene expression based tumor classification and a corresponding program Tclass were developed. The proposed method was applied to a public gene expression data set for colon cancer that consists of 22 normal and 40 tumor colon tissue samples to evaluate its performance for classification. Preliminary results demonstrated that using only a subset of genes ranging from 3 to 10 can achieve high classification accuracy.


Asunto(s)
Perfilación de la Expresión Génica/estadística & datos numéricos , Neoplasias/clasificación , Neoplasias/genética , Programas Informáticos , Neoplasias del Colon/clasificación , Neoplasias del Colon/genética , Biología Computacional , Análisis de Secuencia por Matrices de Oligonucleótidos/estadística & datos numéricos
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