scispace - formally typeset
B

Bino John

Researcher at University of Pittsburgh

Publications -  26
Citations -  11158

Bino John is an academic researcher from University of Pittsburgh. The author has contributed to research in topics: RNA & Gene. The author has an hindex of 18, co-authored 25 publications receiving 10188 citations. Previous affiliations of Bino John include Rockefeller University & State University of New York System.

Papers
More filters
Journal ArticleDOI

Human MicroRNA Targets

TL;DR: This work has predicted target sites on the 3′ untranslated regions of human gene transcripts for all currently known 218 mammalian miRNAs to facilitate focused experiments and suggests that miRNA genes, which are about 1% of all human genes, regulate protein production for 10% or more of allhuman genes.
Journal ArticleDOI

MicroRNA targets in Drosophila

TL;DR: The results reaffirm the thesis that miRNAs have an important role in establishing the complex spatial and temporal patterns of gene activity necessary for the orderly progression of development and suggest additional roles in the function of the mature organism.
Journal ArticleDOI

Identification of Virus-Encoded MicroRNAs

TL;DR: The small RNA profile of cells infected by Epstein-Barr virus is recorded and it is shown that EBV expresses several microRNA (miRNA) genes, which are identified viral regulators of host and/or viral gene expression.
Journal ArticleDOI

Tools for comparative protein structure modeling and analysis

TL;DR: The following resources for comparative protein structure modeling and analysis are described (http://salilab.org): MODELLER, a program for comparative modeling by satisfaction of spatial restraints, and MODWEB, a web server for automated comparative modeling that relies on PSI-BLAST, IMPALA and ModeLLER.
Journal ArticleDOI

Comprehensive Polyadenylation Site Maps in Yeast and Human Reveal Pervasive Alternative Polyadenylation

TL;DR: The correlation level between sense and antisense transcripts to depend on gene expression levels, supporting the view that overlapping transcription from opposite strands may play a regulatory role and the data provide a comprehensive view of the polyadenylation state and overlapping transcription.