RapidMic: Rapid Computation of the Maximal Information Coefficient | Zendy

Dongming Tang | Zendy; Mingwen Wang | Zendy; Weifan Zheng | Zendy; Hongjun Wang | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

RapidMic: Rapid Computation of the Maximal Information Coefficient

Author(s) -

Dongming Tang,

Mingwen Wang,

Weifan Zheng,

Hongjun Wang

Publication year - 2014

Publication title -

evolutionary bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.502

H-Index - 32

ISSN - 1176-9343

DOI - 10.4137/ebo.s13121

Subject(s) - computation , computer science , code (set theory) , scale (ratio) , source code , data mining , parallel processing , algorithm , parallel computing , programming language , physics , set (abstract data type) , quantum mechanics

To discover relationships and associations rapidly in large-scale datasets, we propose a cross-platform tool for the rapid computation of the maximal information coefficient based on parallel computing methods. Through parallel processing, the provided tool can effectively analyze large-scale biological datasets with a markedly reduced computing time. The experimental results show that the proposed tool is notably fast, and is able to perform an all-pairs analysis of a large biological dataset using a normal computer. The source code and guidelines can be downloaded from https://github.com/HelloWorldCN/RapidMic.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research