CrossPlan: systematic planning of genetic crosses to validate mathematical models | Zendy

Aditya Pratapa | Zendy; Neil Adames | Zendy; Pavel Kraikivski | Zendy; Nicholas Franzese | Zendy; John J. Tyson | Zendy; Jean Peccoud | Zendy; T. M. Murali | Zendy

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CrossPlan: systematic planning of genetic crosses to validate mathematical models

Author(s) -

Aditya Pratapa,

Neil Adames,

Pavel Kraikivski,

Nicholas Franzese,

John J. Tyson,

Jean Peccoud,

T. M. Murali

Publication year - 2018

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bty072

Subject(s) - computer science , set (abstract data type) , workflow , source code , process (computing) , mutation , integer (computer science) , genetic algorithm , computational biology , data mining , biology , machine learning , genetics , gene , programming language , database

Mathematical models of cellular processes can systematically predict the phenotypes of novel combinations of multi-gene mutations. Searching for informative predictions and prioritizing them for experimental validation is challenging since the number of possible combinations grows exponentially in the number of mutations. Moreover, keeping track of the crosses needed to make new mutants and planning sequences of experiments is unmanageable when the experimenter is deluged by hundreds of potentially informative predictions to test.

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