Table Of ContentGene Regulation and Metabolism
Computational Molecular Biology
Sorin Istrail, Pavel Pevzner, and Michael Waterman, editors
Computational Methods for Modeling Biochemical Networks
James M. Bower and Hamid Bolouri, editors, 2000
Computational Molecular Biology: An Algorithmic Approach
Pavel A. Pevzner, 2000
Current Topics in Computational Molecular Biology
Tao Jiang, Ying Xu, and Michael Q. Zhang, editors, 2002
Gene Regulation and Metabolism: Postgenomic Computational Approaches
Julio Collado-Vides and Ralf Hofesta¨dt, editors, 2002
Microarrays for an Integrative Genomics
Isaac S. Kohane, Alvin Kho, and Atul J. Butte, 2002
Gene Regulation and Metabolism
Postgenomic Computational Approaches
edited by Julio Collado-Vides and Ralf Hofesta¨dt
A Bradford Book
The MIT Press
Cambridge, Massachusetts
London, England
(2002MassachusettsInstituteofTechnology
Allrightsreserved.Nopartofthisbookmaybereproducedinanyformbyanyelectronic
ormechanicalmeans(includingphotocopying,recording,orinformationstorageandre-
trieval)withoutpermissioninwritingfromthepublisher.
ThisbookwassetinPalatinoon3B2byAscoTypesetters,HongKongandwasprinted
andboundintheUnitedStatesofAmerica.
LibraryofCongressCataloging-in-PublicationData
Generegulationandmetabolism:postgenomiccomputationalapproaches/editedby
JulioCollado-Vides&RalfHofesta¨dt.
p. cm.— (Computationalmolecularbiology)
Includesbibliographicalreferencesandindex.
ISBN0-262-03297-X(hc.:alk.paper)
1.Genetics—Mathematicalmodels. 2.Molecularbiology—Mathematicalmodels.
I.Collado-Vides,Julio. II.Hofesta¨dt,Ralf. III.Series.
QH438.4.M3G462002
572.800105118—dc21 2001056247
Contents
Preface vii
1 Are the Eyes Homologous? 1
Jeremy C. Ahouse
I Information and Knowledge Representation 17
2 Automation of Protein Sequence Characterization and Its
Application in Whole Proteome Analysis 19
Rolf Apweiler, Margaret Biswas, Wolfgang Fleischmann, Evgenia
V. Kriventseva, and Nicola Mulder
3 Information Fusion and Metabolic Network Control 49
Andreas Freier, Ralf Hofesta¨dt, Matthias Lange, and Uwe Scholz
II Gene Regulation: From Sequence to Networks 85
4 Specificity of Protein-DNA Interactions 87
Gary D. Stormo
5 Genomics of Gene Regulation: The View from Escherichia coli 103
Julio Collado-Vides, Gabriel Moreno-Hagelsieb, Ernesto
Pe´rez-Rueda, Heladia Salgado, Araceli M. Huerta, Rosa Mar´ıa
Gutie´rrez, David A. Rosenblueth, Andre´s Christen, Esperanza
Ben´ıtez-Bello´n, Arturo Medrano-Soto, Socorro Gama-Castro,
Alberto Santos-Zavaleta, Ce´sar Bonavides-Mart´ınez, Edgar
D´ıaz-Peredo, Fabiola Sa´nchez-Solano, and Dulce Mar´ıa Milla´n
6 Discovery of DNA Regulatory Motifs 129
Abigail Manson McGuire and George M. Church
7 Gene Networks Description and Modeling in the GeneNet
System 149
Nikolay A. Kolchanov, Elena A. Ananko, Vitali A. Likhoshvai,
Olga A. Podkolodnaya, Elena V. Ignatieva, Alexander V.
Ratushny, and Yuri G. Matushkin
8 Regulation of Cellular States in Mammalian Cells from a
Genomewide View 181
Sui Huang
III Postgenomic Approaches 221
9 Predicting Protein Function and Networks on a
Genomewide Scale 223
Edward M. Marcotte
10 Metabolic Pathways 251
Steffen Schmidt and Thomas Dandekar
11 Toward Computer Simulation of the Whole Cell 273
Masaru Tomita
Glossary 289
Corresponding Authors 297
Index 299
vi Contents
Preface
Weareinthemiddleofagenomeperiodmarkedbythefullsequencing
of complete genomes. Last year (2001) will be identified in the history
of biology by the publication of the first draft of the complete sequence
ofthehumangenome.Muchworkstillliesaheadtoachievethegoalof
fully finishing many of these eukaryotic and prokaryotic genomes that,
as published, still contain gaps.
At a first glance, genomics has not produced a strong conceptual
change in biology. The fundamental problems remain: understanding
the origin of life, the complex organization of a cell, the pathways of
differentiation, aging, and the molecular and cellular bases for the
capabilities of the brain. What has happened is an explosion of molec-
ularinformation;genomicsequenceswillbefollowedinthenearfuture
by exhaustive catalogs of protein interactions and protein function (as
proteomicstakesthelead). Thiswealth ofinformation can be analyzed,
visualized, and manipulated only with the help of computers. This
basic contribution of computers was initially not recognized by biolo-
gists. Certainly, by the time of the beginning of GenBank, in the 1980s,
the experimentalist could imagine an institute where computational bi-
ology was merely technical support for databases and access to Gen-
Bank, and maybe a classic Bohering metabolic chart hung on the wall
(initiated in the 1960s by G. Michal). The influence of genomes is such
that today what Franc¸oisJacob conceived as theMouseInstitutewould
do much better having on staff experimentalists, computer scientists,
statisticians, mathematicians, and computational biologists. We have
reachedapointwherebiologyarticlesarepublishedwithcontributions
from researchers who recently were, for instance, computer scientists
working in logic programming.
This is no small change if we remember the place of theoretical and
mathematical biology as an activity that could be fascinating, but to
a large extent was done in isolation, having little influence on main-
stream experimental molecular biology. Today, the student, post-
doctoralfellow,orevenyoungprofessorwhoisknowledgeableboth in
biology and in computer science has much broader opportunities. Gen-
omics may really be opening the door to a more profound conceptual
change in the way we study living systems in the laboratory.
With a foot in sequence analysis, this book is centered on current
computational approaches to metabolism and gene regulation. This is
an area of computational biology that welcomes new methods, ideas,
and approaches with the goal of generating a better understanding of
the complex networks of metabolic and regulatory capabilities of the
cell. Classical concepts have to be redefined or clarified to address the
study ofthegeneticsof populationsand ofthebiochemicalinteractions
and regulatory networks organizing a living system. Given the con-
stant and pervading importance of comparative genomics, these con-
cepts must be precise when comparing genes, proteins, and systems
across different species.
The first chapter, by Jeremy Ahouse, is an exercise in thinking about
the concept of homology (the common origin of similarities) in order to
use it adequately when considering homologous networks of gene reg-
ulation between species.
Currently, DNA sequence data is the most abundant material with
whichtobeginaprojectincomputationalbiology.Rawsequencesfrom
genomes have to be analyzed and annotated, in ways that improve
continuously as the databases expand and sharper methods are used.
The second chapter, by Rolf Apweiler and colleagues, describes an
integrated system for this task. Databases centering on specific signals,
motifs, or structures have exploded in number in the last years. The
databases describe those pieces of macromolecules whose function we
know, and therefore are essential for algorithmic analyses. The third
chapter, by the team of Ralf Hofesta¨dt, shows a system capable of in-
tegrating data from different databases, and its subsequent use in the
integration and modeling of metabolic pathways using a rule-based
system.
Once the computational and basic annotations are in place, we can
move from sequences to networks of gene regulation and cell differen-
viii Preface
tiation. The second part of the book begins with chapter 4, by Gary
Stormo, who describes the foundations of weight matrices and their
biophysical interpretation in protein-DNA interactions. In a way, this
method and its variants are for regulatory motifs what the Smith-
Waterman algorithm was for coding sequence comparisons. Defining
the best matrix is based on the problem of defining the best multiple
alignment,giventheconstraints ofno gaps, symmetry,andotherprop-
erties describing most protein-DNA binding sites in upstream regions.
Abigail McGuire and George Church, in chapter 6, show how the inte-
gration of gene regulation has to be supported by experimental studies
oftranscriptomeanalysescombinedwithcomputationalmotifsearches.
Chapter 5, by Julio Collado-Vides and colleagues, is devoted to com-
putational studies of gene regulation in E. coli in which different pieces
are put together, making it feasible to think of a global computational
study of a complete network of transcription initiation in a cell. A
pair of chapters illustrate the complexity of these issues when studying
eukaryotes, as seen in the signal transduction modeling by Nikolay
Kolchanov and colleagues (chapter 7), and by the Boolean network
methodology and its plausible application to modeling the network of
factors involved in the biology of asthma by Sui Huang (chapter 8).
In chapter 9 Edward Marcotte presents a relatively novel approach
using phylogenetic profiles to define a quantitative definition of func-
tion in genomics. This is a powerful method that does not require
homology among genes to identify groups of genes involved in the
same function. Metabolic flux analysis as well as the comparison of
pathways in different genomes is illustrated in chapter 11, by Steffen
Schmidt and Thomas Dandekar. The book ends with a chapter by
Masaru Tomita that describes a more ambitious modeling that inte-
grates metabolism, regulation, translation, and membrane transport. A
comprehensive in silico complete cell model is still in its infancy, but
Tomitapointstowhatliesahead.Stillmoreimportantisevaluatingthe
predictive capability of all these computational modeling and simula-
tion projects.
This book does not attempt to provide a complete account of
this expanding and exciting area of research. Many other databases,
algorithms, and mathematical approaches are enriching postgenomic
computational research. In 1995 and 1998 we participated in the
organization of two Dagstuhl seminars centered on modeling and
ix Preface
