on the ontology of disease part ii n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
ON THE ONTOLOGY OF DISEASE: part II PowerPoint Presentation
Download Presentation
ON THE ONTOLOGY OF DISEASE: part II

Loading in 2 Seconds...

play fullscreen
1 / 60

ON THE ONTOLOGY OF DISEASE: part II - PowerPoint PPT Presentation


  • 124 Views
  • Uploaded on

ON THE ONTOLOGY OF DISEASE: part II. The Philosophy of Biology: Structure, Function, Evolution Louis J. Goldberg University at Buffalo October 28, 2006. the complexity dilemma. mechanistic explanations cannot deal with the ever unfolding distributed complexity of biological reality.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'ON THE ONTOLOGY OF DISEASE: part II' - kenadia


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
on the ontology of disease part ii

ON THE ONTOLOGY OF DISEASE: part II

The Philosophy of Biology: Structure, Function, Evolution

Louis J. GoldbergUniversity at Buffalo

October 28, 2006

the complexity dilemma
the complexity dilemma

mechanistic explanations cannot deal with the ever unfolding distributed complexity of biological reality

complexity equivalence
complexity equivalence

all levels of organization follow the same structural pattern in biological networks (Song et al, 2005).

the base level has equivalent complexity to the level from which it emerges, and the level which will emerge above

networks and
networksand

emergence

hierarchy

granularity

complexity

adaptability

the OBO Foundry

disease

biomedical theories of disease
biomedical theories of disease

humoral

miasmatic

germ

mechanistic

??

the humoral theory of disease
the humoral theory of disease
  • biological basis: there are four bodily fluids, or humors; blood, phlegm, yellow bile, and black bile
  • definition of disease: imbalance among the humors causes disease
the miasmatic theory of disease
the miasmatic theory of disease

miasma: a poisonous vapor or mist filled with particles from decomposed matter (miasmata)

disease: breathing miasma causes disease

be clean and avoid putrescence

the germ theory of disease the modern era begins
the germ theory of diseasethe modern era begins

biological basis: microorganisms exist in nature

definition of disease: microorganisms invade human bodies and are the direct cause of infectious diseases

replaces the humoral and miasmatic theories of disease

modern biomedicine
modern biomedicine

the mechanistic theory of disease

in what do working biomedical scientists believe is there a philosophy of biomedicine
in what do working biomedical scientists believe?is there a philosophy of biomedicine?

biomedical scientists believe:

in cells and the cell doctrine

the cell doctrine proposed in 1838 by matthias schleiden and by theodor schwann
the cell doctrine(proposed in 1838 by Matthias Schleiden and by Theodor Schwann)
  • cells are the fundamental structural and functional units of all organisms
  • all organisms are composed of one or more cells
  • all cells come from preexisting cells
  • all vital functions of an organism occur within cells
  • cells contain the hereditary information necessary for regulating cell functions and for transmitting information to the next generation of cells
in what do working biomedical scientists believe is there a philosophy of biomedicine1
in what do working biomedical scientists believe?is there a philosophy of biomedicine?

biomedical scientists believe:

in cells and the cell doctrine

in mechanistic (scientific) explanations of intracellular function that are based on biochemical/molecular dynamics

that functions and malfunctions at the organism level can be explained by biochemical dynamics at the cellular/molecular level

traditional biomedicine
traditional biomedicine

is thoroughly mechanism focused

is dominated by notions of molecular causality

molecular mechanisms (operations) at the biochemical level lead “upward” to the understanding of health and disease at the organism level

restlessness in biomedicine
restlessness in biomedicine

“During the last fifty years the dominant stance in experimental biology has been reductionism.”

“For the most part, research programs were based on the notion that genes were in 'the driver's seat' controlling the developmental program and determining normalcy and disease (genetic reductionism and genetic determinism).”

“The optimism of molecular biologists, fueled by early success in tackling relatively simple problems, has now been tempered by the difficulties found when attempting to understand complex biological problems.”

Soto AM, Sonnenschein C. J Biosci 2005 Feb:30(1):103-18 Emergentism as a default: cancer as a problem of tissue organization.

the limitations of molecular mechanistic explanations
the limitations of molecular mechanistic explanations

“Although molecular biology offers many spectacular successes, it is clear that the detailed inventory of genes, proteins, and metabolites is not sufficient to understand the cell's complexity.”

Zoltan and Barabasi, Systems biology: life’s complexity pyramid. Science (2002) 298: 763-764.

mechanistic biochemical explanation recedes into the background
mechanistic biochemical explanation recedes into the background

a current trend in biomedical research

the foreground becomes occupied by newly discovered components involved in unsuspected operations

slide21

studies of mechanisms and mechanistic explanations at the molecular level continue

a new omic entity comes into being

network theory is applied to the biomedical domain

the omic entity
the omic entity

out of the interactions of countless instances of particular types there emerges a larger entity that acts as a community of instances which forms new types at a “higher” level of organization

“information storage and processing, and the execution of cell programs, is related to the distinct levels ofomic organization, and not to the operations of biochemical pathways”

Zoltan and Barabasi, Systems biology: life’s complexity pyramid. Science (2002) 298: 763-764

omic levels of organization
omic levels of organization

ome

component parts

discipline

genome DNA genomics

transcriptome RNA transcriptomics

proteome proteins proteomics

metabolome metabolites metabolomics

microbiome microorganisms metagenomics

slide24

G

T

P

this is foundational for all cells: eubacteria, prokaryotes, free-living eukaryotes and eukaryotes in metazoa

Zoltan and Barabasi, Systems biology: life’s complexity pyramid. Science (2002) 298: 763-764.

what does omic thinking add to biomedicine
what does omic thinking add to biomedicine?

it moves from a one-at-a-time mechanistic, test tube view of molecular chemistry, to a population view

it conceives of the type, genome, interacting with the type, transcriptome, to produce the type, proteome

the interactome: the entire set of all omic level components and operations of the cell

beyond omics the network
beyond omics: the network

“…the distinctness of these (the omic) organizational levels has recently come under fire.”

“…viewing the cell as a network of genes and proteins offers a viable strategy for addressing the complexity of living systems.”

Zoltan and Barabasi, Systems biology: life’s complexity pyramid. Science (2002) 298: 763-764.

intracellular organization
intracellular organization

“There is remarkable integration of the various layers both at the regulatory and the structural level. Insights into the logic of cellular organization can be achieved when we view the cell as a complex network in which the components are connected by functional links.”

Zoltan and Barabasi, Systems biology: life’s complexity pyramid. Science (2002) 298: 763-764.

slide29
map of the C. elegans interaction network, or "interactome," links 2,898 proteins (nodes) by 5,460 interactions (edges

Li, S. A Map of the Interactome Network of the Metazoan C. elegans.Science (2004) 303: 540 - 543.

a map of the interactome network of the metazoan c elegans science 2004 303 540 543
A Map of the Interactome Network of the Metazoan C. elegans.Science (2004) 303: 540 - 543.

Li,1* Christopher M. Armstrong,1* Nicolas Bertin,1* Hui Ge,1* Stuart Milstein,1* Mike Boxem,1* Pierre-Olivier Vidalain,1* Jing-Dong J. Han,1* Alban Chesneau,1,2* Tong Hao,1 Debra S. Goldberg,3 Ning Li,1 Monica Martinez,1 Jean-Fran腔is Rual,1,4 Philippe Lamesch,1,4 Lai Xu,5 Muneesh Tewari,1 Sharyl L. Wong,3 Lan V. Zhang,3 Gabriel F. Berriz,3 Laurent Jacotot,1 Philippe Vaglio,1 J Reboul,1 Tomoko Hirozane-Kishikawa,1 Qianru Li,1 Harrison W. Gabel,1 Ahmed Elewa,1|| Bridget Baumgartner,5 Debra J. Rose,6 Haiyuan Yu,7 Stephanie Bosak,8 Reynaldo Sequerra,8 Andrew Fraser,9 Susan E. Mango,10 William M. Saxton,6 Susan Strome,6 Sander van den Heuvel,11 Fabio Piano,12 Jean Vandenhaute,4 Claude Sardet,2 Mark Gerstein,7 Lynn Doucette-Stamm,8 Kristin C. Gunsalus,12 J. Wade Harper,5 Michael E. Cusick,1 Frederick P. Roth,3 David E. Hill,1ヲ Marc Vidal1ヲ#

graphical representation of a highly interconnected subnetwork
Graphical representation of a highly interconnected subnetwork

Li, S. A Map of the Interactome Network of the Metazoan C. elegans.Science (2004) 303: 540 - 543.

slide32
TWO EXAMPLES OF RECENT RESEARCH STUDIES EXEMPLIFYING THE NEW APPROACH:GOING FROM MOLECULES TO CELLS TO ORGANISMS

Sporns, O., Chialvo, D. R., Kaiser, M. and Hilgetag, C. C. (2004) Organization, development and function of complex brain networks, Trends Cogn Sci,8, 418-25

Andrew J Pocklington, Mark Cumiskey, J Douglas Armstrong and Seth G N Grant, (2006) The proteomes of neurotransmitter receptor complexes form modular networks with distributed functionality underlying plasticity and behaviour, Molecular Systems Biology2. Published online: 17 January 2006
Article number: 2006.0023

the universal nature of networks
the universal nature of networks

the general principles in the structural and functional organization of complex networks are shared by various natural, social and technological systems

the interaction of architecture (the network's connection topology) and dynamics (the behavior of the individual network nodes), gives rise to global states[new continuants] and ‘emergent’ behaviors [new occurrents].”

Sporns, O., Chialvo, D. R., Kaiser, M. and Hilgetag, C. C. (2004) Organization, development and function of complex brain networks, Trends Cogn Sci,8, 418-25

general network characteristics
general network characteristics

networks are sets of nodes linked by connections

In many networks, clusters of nodes segregate into tightly coupled neighborhoods, but maintain very short DISTANCES among nodes across the entire network, giving rise to a small world within the network.

The degree to which individual nodes are connected forms a distribution that, for many but not all networks, decays as a power law, producing a SCALE-FREE architecture characterized by the existence of highly connected nodes (hubs).

Sporns, O., Chialvo, D. R., Kaiser, M. and Hilgetag, C. C. (2004) Trends Cogn Sci,8, 418-25.

sporn asks
Sporn asks

what is the structural substrate of neuroanatomy and how does it relate to the more dynamic functional and effective connectivity patterns that underlie human cognition?

Sporn believes that “network analysis offers new fundamental insights into global and integrative aspects of brain function, including the origin of flexible and coherent cognitive states within the neural architecture.”

slide37

Small-world and scale-free structural and functional brain networks.

Sporns, O., Chialvo, D. R., Kaiser, M. and Hilgetag, C. C. (2004) Trends Cogn Sci,8, 418-25

postsynaptic density psd
POSTSYNAPTIC DENSITY (PSD)

post synaptic density-electron dense cytoskeletal specialization located on the post synaptic membrane at the site of synaptic contact.

slide39

TEXTBOOK VIEW OF SYNAPSE

Nolte, Human Brain, Fig. 8.4

the psd
the PSD

macromolecular complexes of neurotransmitter receptors

comprised of over 1000 proteins

perhaps the most complex molecular structures known in mammals

proteins in these structures participate in information processing in the brain, and also play roles in disease

the pocklington study
The Pocklington study

determine the organization and function of the mammalian neurotransmitter receptor complexN-methyl-d-aspartate (NRC/MASC) using a systems biology approach.

a) use synapse proteomic data to present a detailed analysis of the MASC complex using annotation, network and statistical approaches.

b) develop a model to explain the structural and functional aspects of synapse molecular complexity

Pocklington et al., The proteomes of neurotransmitter receptor complexes form modular networks with distributed functionality underlying plasticit an behaviour, Molecular Systems Biology2. Published online: 17 January 2006Article number: 2006.0023

slide43

reductionist methods

bioinformatics/ ontology

graph theory and network analysis

Fig. 1Pocklington et al., The proteomes of neurotransmitter receptor complexes form modular networks with distributed functionality underlying plasticity and behaviour, Molecular Systems Biology2. Published online: 17 January 2006Article number: 2006.0023

modular structure and functional organization of the masc n methyl d aspartate receptor complex
Modular structure and functional organization of the MASC (N-methyl-d-aspartate receptor complex)
  • proteins are clustered into modules
  • individual modules play multiple functional roles
  • this permits distribution of information processing and regulation of effector pathways over multiple modules
  • there is a dynamical balance between multiple functional processes
  • synchronization of multiple cell-biological processes induces synaptic plasticity that is
  • manifested at a higher levels of neurological function through behavioural learning

Fig. 5Pocklington et al., The proteomes of neurotransmitter receptor complexes form modular networks with distributed functionality underlying plasticity and behaviour, Molecular Systems Biology2. Published online: 17 January 2006Article number: 2006.0023

slide45

Network cluster analysis. Clustering of the largest connected component of the MASC network identified 13 clusters.

50% of its proteins are essential to normal synaptic plasticity; 40% are implicated in schizophrenia; cognitive function

assimilates signals; co-ordinates common effector mechanisms

hippocampus
HIPPOCAMPUS

Nolte Fig 32-15

the behavioral level
the behavioral level

cognitive processes

what makes biological complexity work
what makes biological complexity work?

high quality components (atoms and molecules)

formal language (physical chemistry)

common architecture (physical rules of network assembly)

stability of macro-assemblies (network physics)

because of the above, networks can stack (platform stability)

is there semantic interoperability in biological networks? a) at a single level: the GTP? b) between levels: PSD and behavior?

weakness in biological complexity
weakness in biological complexity?

network multiplication: large systems (the human organism) are composed of multiple, semi-independent networks

it becomes difficult to maintain the coordination of marginally connected networks (e.g. metagenomics: the interface between the microbial genome and the organism’s cell genome)

destructive competition between networks can occur

the obo foundry
the OBO foundry
  • a family of interoperable gold standard biomedical reference ontologies to serve the annotation of inter alia
    • scientific literature
    • model organism databases
    • clinical trial data
the obo foundry1
THE OBO FOUNDRY

undergoing reform

Gene Ontology (GO)

Chemical Ontology (ChEBI)

Cell Ontology (CL)

Foundational Model of Anatomy (FMA)

Phenotype Quality Ontology (PaTO)

Sequence Ontology (SO)

new

Common Anatomy Reference Ontology (CARO)

Clinical Trial Ontology (CTO)

Functional Genomics Investigation Ontology (FuGO)

Protein Ontology (PrO)

RNA Ontology (RnaO)

Relation Ontology (RO )

under consideration

disease ontology (DO)

biomedical image ontology (BIO)

upper biomedical ontology (OBO UBO)

environmental ontology (EnvO)

systems biology ontology (SBO)

criteria
criteria

a common formal language

for any particular domain, there is community convergence on a single controlled vocabulary.

the ontology has a clearly specified and clearly delineated content

common architecture: The ontology uses relations which are unambiguously defined following the pattern of definitions laid down in the OBO Relation Ontology

the developers of each ontology commit to its maintenance in light of scientific advance: annotation

disease ontology do
disease ontology (DO)

does not belong in the OBO foundry

we do not now have a unified theory of disease

there can only be the category, ontologies of disease, under which are listed the ontologies of specific diseases (e.g. multiple sclerosis MSO)

if the OBO foundry is constructed properly, then, as our understanding of disease changes, old names can disappear (in ten years, there may not be a disease we call MS) and new ones appear

permitting the foundry to persist

the structural organization of ontologies in the foundry
the structural organization of ontologies in the foundry

is nonexistent

which makes it all the more crucial that the criteria be met

the boundaries between ontologies will reconfigure (self-assemble) as our understanding of biology changes

tracking emerging organization and information flows within the network of ontologies
tracking emerging organization and information flows within the network of ontologies

will they conform to the principles of organization and function found in other complex structures?

will we be able to identify nodes, modules, networks, etc?

complexity and the obo foundry
complexity and the OBO foundry

is it appropriate to think of the suite of interoperable biomedical ontologies currently being forged in the OBO foundry as an evolving network?

will the network “give rise to global states and ‘emergent’ behaviors” the nature of which are unpredictable?

formation of a new network
formation of a new network

will creation of massively interoperable biomedical ontologies that are semantically interoperable with human minds be the equivalent of the creation of a new network in nature not unlike those that currently exist in biological organisms?

is semantic interoperability to be found in the interaction of the human cognitive network with the computer-based foundry network which it is constructing?

will the network “give rise to global states and ‘emergent’ behaviors” the nature of which are unpredictable?

slide60

human understanding

semantic interoperability

biological reality

Foundry network

computer systems

biomedical science

ontology

biochemistry

network analysis

primary scientific lit

annotation