Abstract Background A logical model of the known metabolic processes in <it>S. cerevisiae </it>was constructed from iFF708, an existing Flux Balance Analysis (FBA) model, and augmented with information from the KEGG online pathway database. The use of predicate logic as the knowledge representation for modelling enables an explicit representation of the structure of the metabolic network, and enables logical inference techniques to be used for model identification/improvement. Results Compared to the FBA model, the logical model has information on an additional 263 putative genes and 247 additional reactions. The correctness of this model was evaluated by comparison with iND750 (an updated FBA model closely related to iFF708) by evaluating the performance of both models on predicting empirical minimal medium growth data/essential gene listings. Conclusion ROC analysis and other statistical studies revealed that use of the simpler logical form and larger coverage results in no significant degradation of performance compared to iND750.</p

KE Whelan

RD King

CH Bryant

PGK Reiser

G Giaever

NC Duarte

J Förster

H Kitano

ME Csete

L Chong

EH Davidson

M Kanehisa

PD Karp

X Feng

P Mendes

M Tomita

JS Edwards

R Mahadevan

ND Duarte

KJ Kauffman

D Segre

T Shlomi

J Stelling

N Lemke

I Bratko

F Fages

C Gershenson

S Kauffman

B Kuipers

PA Flach

S Muggleton

SS Dwight

E Gasteiger

RG Sargent

English

PubMed

Springer - Publisher Connector

Using a logical model to predict the growth of yeast

The scandals surrounding organ removal and retention throughout the United Kingdom provoked several Inquiries and ultimately led to law reform. Although the medical professions were well represented at the Inquiries, little was heard of the voices of those at the ‘coal face’. In this scoping study, funded by the Wellcome Trust, we interviewed a number of doctors and others engaged in the uses of human tissue and organs to explore their hopes, concerns and fears about the role of the law in their practices. We found that those involved in transplantation were more aware of, and more actively involve with, the law, whereas others, such as pathologists, had less direct engagement with the law. Most of those we interviewed expressed the hope that law reform would provide much-needed clarity. Although some expressed concern that the law might be over-intrusive, most felt that the placing of authority firmly in the hands of the person him or her self to decide what should happen to their bodies was to be welcomed.The scandals surrounding organ removal and retention throughout the United Kingdom provoked several Inquiries and ultimately led to law reform. Although the medical professions were well represented at the Inquiries, little was heard of the voices of those at the ‘coal face’. In this scoping study, funded by the Wellcome Trust, we interviewed a number of doctors and others engaged in the uses of human tissue and organs to explore their hopes, concerns and fears about the role of the law in their practices. We found that those involved in transplantation were more aware of, and more actively involve with, the law, whereas others, such as pathologists, had less direct engagement with the law. Most of those we interviewed expressed the hope that law reform would provide much-needed clarity. Although some expressed concern that the law might be over-intrusive, most felt that the placing of authority firmly in the hands of the person him or her self to decide what should happen to their bodies was to be welcomed

McLean, SAM

Campbell, AV

Gutridge, KL

Harper, H

Explore Bristol Research

Human tissue legislation and medical practice: a benefit or a burden?

Background: A logical model of the known metabolic processes in S. cerevisiae was constructed from iFF708, an existing Flux Balance Analysis (FBA) model, and augmented with information from the KEGG online pathway database. The use of predicate logic as the knowledge representation for modelling enables an explicit representation of the structure of the metabolic network, and enables logical inference techniques to be used for model identification/improvement. Results: Compared to the FBA model, the logical model has information on an additional 263 putative genes and 247 additional reactions. The correctness of this model was evaluated by comparison with iND750 (an updated FBA model closely related to iFF708) by evaluating the performance of both models on predicting empirical minimal medium growth data/essential gene listings. Conclusion: ROC analysis and other statistical studies revealed that use of the simpler logical form and larger coverage results in no significant degradation of performance compared to iND750

King, Ross Donald

Whelan, Ken

Aberystwyth Research Portal

The scandals surrounding organ removal and retention throughout the United Kingdom provoked several Inquiries and ultimately led to law reform. Although the medical professions were well represented at the Inquiries, little was heard of the voices of those at the ‘coal face’. In this scoping study, funded by the Wellcome Trust, we interviewed a number of doctors and others engaged in the uses of human tissue and organs to explore their hopes, concerns and fears about the role of the law in their practices. We found that those involved in transplantation were more aware of, and more actively involve with, the law, whereas others, such as pathologists, had less direct engagement with the law. Most of those we interviewed expressed the hope that law reform would provide much-needed clarity. Although some expressed concern that the law might be over-intrusive, most felt that the placing of authority firmly in the hands of the person him or her self to decide what should happen to their bodies was to be welcomed

McLean, S.

Campbell, A.

Gutridge, K.

Harper, H.

Enlighten

Human tissue legislation and medical practice: A benefit or a burden?

Crossref

Background: A logical model of the known metabolic processes in S. cerevisiae was constructed from iFF708, an existing Flux Balance Analysis (FBA) model, and augmented with information from the KEGG online pathway database. The use of predicate logic as the knowledge representation for modelling enables an explicit representation of the structure of the metabolic network, and enables logical inference techniques to be used for model identification/improvement. Results: Compared to the FBA model, the logical model has information on an additional 263 putative genes and 247 additional reactions. The correctness of this model was evaluated by comparison with iND750 (an updated FBA model closely related to iFF708) by evaluating the performance of both models on predicting empirical minimal medium growth data/essential gene listings. Conclusion: ROC analysis and other statistical studies revealed that use of the simpler logical form and larger coverage results in no significant degradation of performance compared to iND750. © 2008 Whelan and King; licensee BioMed Central Ltd

Whelan, K. E.

King, R. D.

The University of Manchester - Institutional Repository

A database for post-genome analysis. Trends Genet

Bairoch A: ExPaSy: The proteomics server for in-depth protein knowledge and analysis.

Biochemistry by numbers: simulation of biochemical pathways with Gepasi 3. Trends Biochem Sci

Classification of Random Boolean Networks

DB: Numerical optimisation and simulation for rational metabolic engineering.

DeRaedt L: Inductive Logic Programming: Theory and Methods.

Dor Reis AN, Mombach JC: Essentiality and damage in metabolic networks. Bioinformatics

EcoCyc:Encyclopedia of Escherichia coli genes and metabolism. Nucleic Acid Res

FJ: Dynamic Flux Balance Analysis of Diauxic Growth in Escherichia coli.

Functional Genomic Hypothesis Generation and Experimentation by a Robot Scientist. Nature

Functional profiling of the Saccharomyces cerevisiae genome. Nature

Genome-Scale Reconstruction of the Saccharomyces cerevisiae Metabolic Network. Genome Research

GM: Analysis of optimality in natural and perturbed metabolic networks.

Goto S: KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res

H: A Genomic Regulatory Network for Development. Science

Hutchinson JC: E-CELL: software environment for whole-cell simulation. Bioinformatics

JM: Saccharomyces genome database: underlying principles and organisation. Brief Bioinform

JS: Advances in flux balance analysis. Current Opinion in Biotechnology

Kell DB: Nonlinear optimisation of metabolic pathways: applications to metabolic engineering and parameter estimation. Bioinformatics

Large Scale Evaluation of insilico gene knockouts in Saccharomyces cerevisiae Omics.

Metabolic flux balance analysis and the in silico analysis of Escherichia coli K-12 gene deletions.

Metabolic network structure determines key aspects of functionality and regulation. Nature

Modelling and querying interaction networks in the biochemical abstract machine BIOCHAM.

Mombach JC: A method to identify essential enzymes in the metabolism: application to Escherichia Coli.

On the use of qualitative reasoning to simulate and identify metabolic pathways. Bioinformatics

Palsson BO: Global Reconstruction of the Human Metabolic Network based on Genomic and Bibliomic Data. Proc Natl Acad Sci USA

Prolog Programming for Artificial Intelligence

Qualitative Reasoning

Rabitz H: Optimal Identification of Biochemical Reaction Networks.

Rattei T: MIPS: Analysis and annotation of genome information in

Ray LB: Whole-istic Biology. Science

RD: Combining inductive logic programming, active learning, and robotics to discover the function of genes.

Reconstruction an Validation of Saccharomyces cerevisiae iND750, a Fully Compartmentalized Genome-Scale Metabolic Model. Genome Res

Ruppin E: Regulatory on/off minimization of metabolic flux changes after genetic perturbations.

SG: Developing a logical model of yeast metabolism.

Systems Biology: Systems Biology: A Brief Overview. Science

The Geometry of ROC Space: Understanding Machine Learning Metrics through ROC Isometrics.

Troein C: Random Boolean network models and the yeast transcriptional network. Proc Natl Acad Sci USA

Validation and Verification of Simulation Models.

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Using a logical model to predict the growth of yeast

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