DIMACS Mini-Workshop on System Based Modeling in Informatics

February 19 - 20, 2001
DIMACS Center, Rutgers University, Piscataway, New Jersey

Organizers:
Michael Liebman, Abramson Family Cancer Center, University of Pennsylvania, School of Medicine, liebmanm@mail.med.upenn.edu
Richard L.X. Ho, R.W. Johnson Pharmaceutical Research Institute, RHo@prius.jnj.com
Presented under the auspices of the Special Year on Computational Molecular Biology.

Abstracts:


1.

NIGMS Funding Opportunities for Quantitative Approaches to 
Biomedical Research

James J. Anderson, NIGMS

The National Institute of General Medical Sciences (NIGMS: a component of 
the U.S. National Institutes of Health), in conjunction with other 
Institutes and the National Science Foundation, has issued a number of 
program announcements (PA) and requests for applications (RFA) that provide 
for the support of cross-disciplinary research, education, and training 
involving quantitative approaches to complex biological and biomedical 
problems.  The suite of initiatives have as their foci:
1. The understanding of system principles and dynamics in processes 
involving large numbers of interacting components, at all levels of 
biological organization.

2. The development of analytical methodologies to discover the genetic 
architecture of complex genetic traits.

3. The study of the evolutionary dynamics of pathogens and their hosts with 
their environments.

4. The development of enabling technologies useful for the study of 
metabolic processes and metabolic engineering.

5. The development of basic mathematical concepts and algorithms that have 
the potential for significantly advancing the state of the art in 
biomedical research.

The initiatives comprise mechanisms to fund research projects (traditional 
research project grants (R01) and program project grants (P01)), to fund 
establishment of integrative research efforts ("glue grants," R24), to fund 
extensive programs of research related activities (Center grants (P50)), to 
provide support for short courses and workshops (R25 education grants) for 
both biologists and non-biologists, and to provide training at both pre- 
and postdoctoral level (T32 and T33 Training Grants).
Detailed information on these programs will be available, and can also be 
found at the following URL:http://www.nih.gov/nigms/funding




2.

Analysis of the Global Role of IHF in Transcriptional Regulation
Craig J. Benham
Department of Biomathematical Sciences
Mount Sinai School of Medicine
New York, NY

In a collaboration with Dr. Wes Hatfield (UC-Irvine) we are investigating 
the IHF-regulated ilvPG  promoter.  We have shown that it is activated by a 
mechanism involving the transmission of stress-induced 
destabilization.  Specifically, IHF binding causes a four-fold increase in 
transcriptional initiation rates, but only when the substrate DNA is 
negatively supercoiled.  The mechanism for this activation was elucidated 
by a collaboration between computational analysis of stress-induced 
destabilization and experimental investigations.  When negatively 
supercoiled, a region containing the IHF binding site experiences a 
destabilization of its duplex structure.  IHF binding causes this region to 
reform the B-DNA structure, which causes the destabilization to be 
transferred to the 10 region of the promoter, thereby activating transcription.
This talk will briefly describe the computation of stress-induced 
destabilization.  Then the collaboration will be described by which the 
mechanism of the IHF-regulated ilvPG  promoter was elucidated.  Then we 
indicate how this work is being extended to elucidate the global roles of 
high-affinity IHF binding in transcriptional regulation throughout the E. 
coli genome.  The theoretical analysis of all other known IHF-regulated 
genes finds that they all have destabilization properties that suggest that 
they also could be regulated by the same transmission-type 
mechanism.  Finally, the complete analysis of the entire genome finds a 
total of 125 ORFs with the catenation of properties needed for this 
mechanism.  These results are currently being experimentally tested in Dr. 
Hatfield's lab using expression arrays.  This is the first collaborative 
investigation of a global mechanism of regulation.
This and other work shows that stress-induced strand separation plays 
central roles in the initiation of gene expression. Indeed, recent results 
suggest that it may be among the most archaic regulators of this essential 
biological process.  Speculations will be presented regarding the reasons 
for this importance.



3.

An application framework for modelling biological processes
Carolyn Cho, Physiome Sciences, Princeton NJ USA

The recent increase in the generation and variety of biological data has 
stimulated demand for modeling and simulation to complement experimental 
investigation.  The mathematical expertise required for model building, 
however, has limited its wide-spread application.

Physiome Sciences is developing software and applications for modeling 
signal transduction and other biochemical pathways, intracellular and 
extracellular physiological processes, organs and systems.  These tools 
have expert-user capabilities but are also designed for use by researchers
with no mathematical modeling expertise.  In addition to providing 
hypothesis testing and predictive capabilities, the resulting models become
the entry point for accessing relevant data.  Physiome software provides 
researchers a unified environment to filter information, analyze data, 
develop hypotheses and create a shared knowledge base.

Physiome's modeling framework is designed around 4 core themes.


This presentation focuses on the use of Physiome Sciences' In Silico CellTM
modeling environment to construct, analyze and interpret biochemical 
pathway data. In Silico Cell supports the hierarchical modeling of 
biological systems and the creation of detailed models from simple ones. 
This process is enabled by the use of the CellMLTM modeling language, an 
application of XML for describing biological processes at the cellular and
sub-cellular level.

In Silico Cell's Pathway Editor function allows the researcher to build
and edit pathway diagrams and provides network analysis tools to identify 
possible drug targets at critical points in a biochemical pathway. This is
done using a graphical user interface that automatically generates 
simulations and mathematics from pathway maps. The pathway and its 
individual components are linked to a database that can be referenced and 
updated by the researcher.




4.

Innovative information management software for genetic analysis. 
Richard Groves, Genomica Corporation, Boulder, Colorado 

Genomica provides a unified database structure in which genetic, 
phenotypic, molecular and population-derived information can be stored in a 
single, purpose-built database. Stored data may be visualized, manipulated 
and mined in simple and intuitive data management tools, specifically 
designed for genetic and molecular data. All stored information can be 
rapidly transformed and exported in the rich formats required for further 
research and analysis. Benefits to users include rapid and sophisticated 
data stratification and mining, more time available for data analysis, less 
time spent on data formatting and all data is stored in a single location 
resulting in superior data integrity and security.




5.

Applying In Silico, Animal, and Mental Models of Human Weight Control
Richard L.X. Ho, R.W. Johnson Pharmaceutical Research Institute

There are many ways to study the control of body weight, but all depend on 
having a model with which to construct hypotheses, design experiments, and 
integrate the information for new understanding. To refine their mental 
model of a disease process, researchers traditionally utilize data from 
clinical studies and in vivo animal models. Recently there has been growing 
interest in using in silico models or computer simulations to enhance 
understanding of disease pathophysiology.  A few top-down computer models 
with nonlinear dynamics are now available commercially which allow creation 
of simulated patients and virtual interventions on those patients.  We are 
now using such computer models with data mining software to integrate 
information from low and high throughput methods as well as to help us 
formulate novel hypotheses and experimental designs in the field of human 
weight control.



6.
Pharmacosemiotics: An Emerging Physics/Chemistry/Linguistics Paradigm in 
Pharmacology.  Sungchul Ji, Department of Pharmacology and Toxicology, 
Rutgers University, Piscataway, N.J. 08855.

         Semiotics is the scientific study of signs and symptoms that
was developed originally in Ancient Greece as a means of medical
diagnosis and prognosis. Signs can be macroscopic (e.g., written words
and sentences) or microscopic (e.g., hormones and second messengers)
in size.  Therefore, `pharmacosemiotics,' a term coined by F. E. Yates
in 1999, designates the field of study of drugs viewed as `molecular
signs' with which biomedical scientists can communicate with living
cells in patients to effectuate pharmacotherapy.

         There are two distinct approaches to biomedical research 96
i) the PC paradigm based on the assumption that physics (P) and
chemistry (C) are necessary and sufficient to solve all biomedical
problems, and ii) the PCL paradigm postulating that P and C are
necessary but not sufficient and hence that a new approach,
linguistics (L), must be added to the traditional paradigm in order to
completely describe and understand living phenomena.  The PCL paradigm
is synonymous with the semiotics paradigm, since the study of
molecular signs entails integrating physics, chemistry, and
linguistics.  The semiotics paradigm appears to be strongly supported
by the recent uncovering of the isomorphism between the molecule-based
cell language and the word-based human language [BioSystems 44:17-39
(1997); Ann. N. Y. Acad. Sci. 870:411-417 (1999)].

         The main objective of this contribution is to discuss a 
theoretical model of the living cell known as the Bhopalator that has been 
developed over the past two decades based on the PCL or semiotics paradigm 
[J. Theoret. Biol. 116:399-426 (1985); Comments Toxicol. 5(6): 571-585 
(1997)].  Three groups of concepts, each derived from physics (i), 
chemistry (ii), and linguistics,   played crucial roles in the development 
of the Bhopalator model of the cell  96 i) the notion of solitons or 
soliton-like energetic entities entrapped in biopolymers, ii) the principle  
of self-organizing chemical reaction-diffusion systems, and iii) the 
concept of words and sentences and the associated principle of `double 
articulation.'  The Bhopalator embodying these concepts  predicted i) that  
biopolymers contain sequence-specific conformational strains, called 
`conformons,' that drive all biopolymeric functions,  ii) that the final  
form of expression of structural genes is not polypeptides as is widely 
believed but patterns of concentration and mechanical stress gradients in 
the cytosol and the nucleus, collectively known as `intracellular 
dissipative structures' (IDS's), iiia) that noncoding regions of DNA 
carry `spatiotemporal genes' that control the space- and time-dependent 
evolution of gene expression, and iiib) that IDS's act as molecular analogs of 
`sentences' in the cell, which are essential for cells to execute 
molecular analogs of `propositions,' `arguments,' and `computations.'

         Prediction i) was supported by the discovery by C. Benham of 
`strain induced duplex destabilization or SIDS's in DNA 
[PNAS  90:2999-3003 (1993)].  Prediction ii) is validated by the finding 
reported by Sawyer et  al. that intracellular calcium waves drive chemotaxis 
in neutrophils [Science 230:663-666 (1985)]. Prediction iiia) is substantiate by the
finding of N. Amano et al. that the number of noncoding bases per genome 
increases with the increasing number of transcription factors per 
structural genes in multicellular, but not in unicellular, organisms [Biol.  
Chem. 378:1397-1404 (1997)].  Finally, Prediction in iiib) is consistent 
with the notion of "hyperstructures" proposed by Norris et al. as 
nonequilibrium, transient complexes of biopolymers, metabolites and ions, 
intermediate in size between individual macromolecules and the cell itself,  
that regulate bacterial structure and cell cycle [Biochimie 81:915-920 
(1999)].




7.

Biosimulation: Systems-Based Modeling of Human Physiology in Health and
Disease
Robert J. Leipold, Ph.D.
Modeler - Professional Services
Entelos, Inc.

Compared to other high-tech industries (automotive, aeronautics,
electronics, chemical processing), the pharmaceutical industry has been slow
to adopt systems-based modeling to improve the efficiency and effectiveness
of its operations.  The current process of drug discovery and development is
characterized by long development times, great expense, and a high failure
rate.  Recent technological advances such as expression profiling and
sequence databases have increased the rate at which prospective drug targets
can be identified, but they have done nothing to improve the odds for
success in the subsequent development process.  Entelos offers comprehensive
models of human physiology (PhysioLabs(tm)) within which one can test
prospective targets for effects on clinically-relevant endpoints.
PhysioLabs can be used at every step of the drug discovery and development
process from target selection and prioritization through design and
evaluation of clinical trials.  Examples of these applications will be
illustrated with case studies.




8.

Effective Representation of Gene Families.

Hugh B. Nicholas Jr., David W. Deerfield II., Alexander J. Ropelewski,
and Jaclyn Schwizer.
Pittsburgh Supercomputing Center
440 Fifth Avenue
Pittsburgh, PA 15213

The explosion of sequence data has greatly increased the amount of
information needed to identify distant homologues to a query sequence
against the large, constantly increasing, background of essentially
random, unrelated sequences. One effective solution to this problem
would be a non-redundant database of aligned gene family protein
products which preserves the knowledge of the sequence variation to
which a query sequence must be compared.

We have prepared alignments of gene families' protein products using
different practical unguided, automatic methods as well as refining
these alignments by pattern-based methods. We have represented the
alignments by three different profile methods (average, evolutionary,
and bayesian) and hidden markov models. We will present the results
from a comparison of these different alignment and representation
strategies.




9.

KBTool: An approach to managing diverse biological information that 
provides simple, coherent, extensible storage and retrieval.  
Stephen Shaw, Experimental Immunology Branch, National Cancer Institute, 
Bethesda, MD

Information overload is pervasive in modern biology; finding satisfactory 
ways to efficiently capture and manage available information is essential 
both for human comprehension and for automated analysis.   A small fraction 
of that biological knowledge is stored in structured databases that are 
optimal for automated retrieval, analysis and computation.  In contrast, a 
large fraction of that information is present in free-text documents; and 
as implicit knowledge of biological experts.  We have been experimenting 
with an intermediate approach (evolving in a software application we call 
"KBTool") that encodes biological information in a fashion more structured 
than free text, but more flexible and extensible than conventional 
relational databases.   It is closest in concept to an entity-relationship 
approach.   The current implementation has about 100 categories of entities 
(genes, proteins, peptides, bindings sites, phosphorylation sites, 
pathways, molecular assemblies, references, drugs, types of malignancies, 
etc), about 100 kinds of allowed relationships, and more than 50,000 
specific entities.   Utilization is sufficiently simple that we use it to 
encode and retrieve information related to very diverse tasks: conduct of 
biological research, administration of an electronic journal, managing 
references, personal contacts, bookmarks etc.  Because it provides linkage 
of public data, workgroup-specific data, and private data, KBTool maintains 
a coherence that we have been unable to achieve in any other way.  In our 
experience, accumulation of biological expertise into a machine-readable 
form will occur not when experts are required to log in information, but 
rather when they find it beneficial to do so.   KBTool is making progress 
towards that goal of users storing information based on "enlightened 
self-interest".




10.

A Systems Approach to Post-Genomic Therapeutic Research

Roland Somogyi, Alan Ableson, Max Kotlyar, Ross Dickson, Evan Steeg
Molecular Mining Corporation, Canada

Integrated analysis of genetic, phenotypic and chemical data will be
required to gain insight into complex diseases, discover novel drugs,
and integrate diagnostics with treatments for individualized therapies.
Recent developments in molecular biology, measurement technologies and
computational performance are making it possible to approach these
challenges from a systems perspective. We must now develop flexible
computational methods for discovering predictive connections between
genes, phenotypes and drugs. These relationships involve complex
non-linear and combinatorial interactions, which cannot be found using
traditional linear inference. We are currently applying our advanced
data mining and modeling procedures to a) predictions in the areas of
drug efficacy, genetic predispositions, diagnostics and toxicology, b)
systematic experimental design to provide the right set of facts that
permit valid analysis, and c) network reverse engineering and in silico
experimentation.




11.

Transcriptome annotation using Gene Ontology nomenclature
Han Xie and Liat Mintz
Bioinformatics, Compugen, Jamesburg, NJ

Advances in genomic sequencing and computational biology have presented a
unique challenge to annotate the transcriptome of different species. Here we
report our efforts in systematically examining the human and rodent
transcriptome. EST, mRNA and genomic sequences are clustered using Compugen
LEADS platform technology (www.labonweb.com, www.cgen.com ) to predict gene
clusters. The standardized gene ontology (GO) nomenclature
(www.geneontology.org) was utilized to designate the functions, cellular
localization and involvement of pathways for transcripts. Annotation
procedures were centered on the sequence and motif homology to GO-annotated
genes. In addition, text-mining techniques and multi-parameter cellular
localization modeling were used to increase the annotation accuracy, and
predict novel annotation. The majority of gene clusters containing mRNA
sequences have been assigned GO. This systematic annotation of transcriptome
will help discover new gene functionality as well as facilitate higher-order
analysis of biological systems.




12.

Recurrence Quantification as Tool for Protein Bioinformatics
Joseph P. Zbilut, Professor, Molecular Biophysics and Physiology,
Rush Medical College, Chicago, IL

Recurrence quantification analysis (RQA), a methodology
related to contact maps which extends analyses to higher
dimensions, has been used to understand proteins in a variety of
contexts. Unlike FFTs, its utility redounds from its ability to
quantify variables without first filtering them through
a mathematical transform. Examples of its use will be
given in the context of prion singularities, structure/acitivity
relationships and protein protperties.
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Document last modified on February 7, 2001.