brody-ayers
Uploaded by
1 SLIDES
109 VUES
10LIKES

Analyzing Metabolic Networks: Topological Features and Genomic Insights

DESCRIPTION

Explore metabolic network topology characteristics and integrate genomic data to predict essentiality of reactions using machine learning. Understand local topology, choke points, and reaction profiles.

1 / 1

Télécharger la présentation

Analyzing Metabolic Networks: Topological Features and Genomic Insights

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Metabolic Network 1) Topology based features • Local topology • Deviations • Choke and load points • Damages 2) Genomic and transcriptomic data ATCGAGTTGCAAT ATAGAA – TGCA-T - Gene expression - Homologous genes reaction 3) Flux balance analysis metabolite - Biomass objective flux Feature creation Features Essentiality classes NNNR PUP NNR NP NS RUP CCV . . . E: Essential 1 E N N: Non-essential N Reactions . . . . . . i 1 4 E 3 . . . . . . i Reaction profile The machine learning system (SVM)  Essential o Trained classifier o o o o o x x o x o x Prediction for the reaction to be essential Non-essential x o x o o Input space Space of the kernel x x o x x

More Related