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Title |
MICO: A meta-tool for prediction of the effects of non-synonymous mutations
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Authors |
Gilliean Lee1 & Chin-Fu Chen2*
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Affiliation |
1Department of Mathematics & Computing, Lander University, Greenwood, SC, 29649; 2Center for Molecular Studies and Office of Bioinformatics and Epidemiology, Greenwood Genetic Center, Greenwood, SC, 29646
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cfchen@ggc.org; *Corresponding authors
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Article Type |
Software
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Date |
Received June 20, 2014; Accepted June 27, 2014; Published July 22, 2014
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Abstract |
The Next Generation Sequencing (NGS) is a state-of-the-art technology that produces high throughput data with high resolution mutation information in the genome. Numerous methods with different efficiencies have been developed to predict mutational effects in the genome. The challenge is to present the results in a balanced manner for better biological insights and interpretation. Hence, we describe a meta-tool named Mutation Information Collector (MICO) for automatically querying and collecting related information from multiple biology/bioinformatics enabled web servers with prediction capabilities. The predicted mutational results for the proteins of interest are returned and presented as an easy-to-read summary table in this service. MICO also allows for navigating the result from each website for further analysis.
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Availability |
http: //mico.ggc.org /MICO
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Citation |
Lee & Chen,
Bioinformation 10(7): 469-471 (2014) |
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Edited by |
P Kangueane
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ISSN |
0973-2063
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Publisher |
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License |
This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License. |