Sensitivity Analysis of Biological Boolean Networks Using Information Fusion Based on Nonadditive Set Functions

BMC Systems Biology 8 (1):92 (2014)
  Copy   BIBTEX

Abstract

An algebraic method for information fusion based on nonadditive set functions is used to assess the joint contribution of Boolean network attributes to the sensitivity of the network to individual node mutations. The node attributes or characteristics under consideration are: in-degree, out-degree, minimum and average path lengths, bias, average sensitivity of Boolean functions, and canalizing degrees. The impact of node mutations is assessed using as target measure the average Hamming distance between a non-mutated/wild-type network and a mutated network.

Other Versions

No versions found

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 97,197

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

How a (Neural) Network Operates.Ilexa Yardley - 2022 - Https://Medium.Com/the-Circular-Theory.

Analytics

Added to PP
2023-09-18

Downloads
5 (#1,718,931)

6 months
5 (#1,295,198)

Historical graph of downloads
How can I increase my downloads?

Author's Profile

Anna Wang
University College London

Citations of this work

No citations found.

Add more citations

References found in this work

No references found.

Add more references