The benefit of intrinsic disorder information in neural network prediction of calmodulin binding targets

Timothy R. O'Connor, J. David Lawson, A. Keith Dunker

Research output: Contribution to conferencePaper

1 Scopus citations

Abstract

Calmodulin is an important calcium dependent signaling protein found in all eukaryotic cells. Binding calcium enables calmodulin to bind its targets: basic, amphipathic α-helices. Such binding regulates the activities of many proteins. Because calmodulin wraps completely around the target helix upon binding, it is hypothesized that disorder of a target helix is an important feature of this process. We have used several sequence derived features of calmodulin binding targets (CBT's), including intrinsic order/disorder predictions, to construct neural networks based on permutations of three or more of these features. The resulting networks demonstrate that the addition of intrinsic order/disorder information always increases the performance of a given neural network predictor. The best predictor generated has a performance of 87.8% true positive prediction and 87.2% true negative prediction.

Original languageEnglish (US)
Pages296-299
Number of pages4
StatePublished - Jan 1 2002
Event2002 International Joint Conference on Neural Networks (IJCNN '02) - Honolulu, HI, United States
Duration: May 12 2002May 17 2002

Other

Other2002 International Joint Conference on Neural Networks (IJCNN '02)
CountryUnited States
CityHonolulu, HI
Period5/12/025/17/02

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ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Cite this

O'Connor, T. R., Lawson, J. D., & Dunker, A. K. (2002). The benefit of intrinsic disorder information in neural network prediction of calmodulin binding targets. 296-299. Paper presented at 2002 International Joint Conference on Neural Networks (IJCNN '02), Honolulu, HI, United States.