nuin's Reczko:M [2 articles]

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DIANA-microT web server: elucidating microRNA functions through target prediction.

Nucleic acids research, Vol. 37, No. Web Server issue. (1 July 2009), pp. W273-276.

by M. Maragkakis, M. Reczko, V. A. Simossis, et al.P. Alexiou, G. L. Papadopoulos, T. Dalamagas, G. Giannopoulos, G. Goumas, E. Koukis, K. Kourtis, T. Vergoulis, N. Koziris, T. Sellis, P. Tsanakas, A. G. Hatzigeorgiou

posted to mirna prediction by nuin on 2009-05-05 22:08:31

along with 6 people and 3 groups jfr PabloMarin daforerog dswan gbloeb guhjy microRNA Journal picks Bioinformatics

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Abstract

Computational microRNA (miRNA) target prediction is one of the key means for deciphering the role of miRNAs in development and disease. Here, we present the DIANA-microT web server as the user interface to the DIANA-microT 3.0 miRNA target prediction algorithm. The web server provides extensive information for predicted miRNA:target gene interactions with a user-friendly interface, providing extensive connectivity to online biological resources. Target gene and miRNA functions may be elucidated through automated bibliographic searches and functional information is accessible through Kyoto ...

Prediction of novel microRNA genes in cancer-associated genomic regions--a combined computational and experimental approach.

Nucleic acids research, Vol. 37, No. 10. (1 June 2009), pp. 3276-3287.

by Anastasis Oulas, Alexandra Boutla, Katerina Gkirtzou, Martin Reczko, Kriton Kalantidis, Panayiota Poirazi

posted to cancer mirna by nuin on 2009-04-02 16:00:35

along with 6 people and 2 groups jfr ppgardne ashishanand samgj daforerog tonamswish Journal picks microRNA

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Abstract

The majority of existing computational tools rely on sequence homology and/or structural similarity to identify novel microRNA (miRNA) genes. Recently supervised algorithms are utilized to address this problem, taking into account sequence, structure and comparative genomics information. In most of these studies miRNA gene predictions are rarely supported by experimental evidence and prediction accuracy remains uncertain. In this work we present a new computational tool (SSCprofiler) utilizing a probabilistic method based on Profile Hidden Markov Models to predict novel miRNA precursors. ...

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nuin's Reczko:M [2 articles]

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