Attribute Exploration of Gene Regulatory Processes

This thesis aims at the logical analysis of discrete processes, in particular of such generated by gene regulatory networks. States, transitions and operators from temporal logics are expressed in the language of Formal Concept Analysis. By the attribute exploration algorithm, an expert or a computer program is enabled to validate a minimal and complete set of implications, e.g. by comparison of predictions derived from literature with observed data. Here, these rules represent temporal dependencies within gene regulatory networks including coexpression of genes, reachability of states, invariants or possible causal relationships. This new approach is embedded into the theory of universal coalgebras, particularly automata, Kripke structures and Labelled Transition Systems. A comparison with the temporal expressivity of Description Logics is made. The main theoretical results concern the integration of background knowledge into the successive exploration of the defined data structures (formal contexts). Applying the method a Boolean network from literature modelling sporulation in Bacillus subtilis is examined. Coregulation and mutual exclusion of genes were checked systematically. Conditions for sporulation were clarified by queries to the generated knowledge base. Finally, we developed an asynchronous Boolean network for extracellular matrix formation and destruction in the context of rheumatoid arthritis. By biologically plausible assumptions, the network was adapted to gene expression data obtained from synovial fibroblast cells stimulated by transforming growth factor beta I or by tumor necrosis factor alpha. The final simulations were analysed by attribute exploration integrating the observed time series in a fine-tuned and automated manner. The resulting temporal rules yielded new contributions to controversially discussed aspects of fibroblast biology and corroborated previously known facts, but also generated new hypotheses regarding literature knowledge.

[1]  Johannes Wollbold,et al.  Conceptual Representation of Gene Expression Processes , 2007, KONT/KPP.

[2]  G R Burmester,et al.  Mononuclear phagocytes and rheumatoid synovitis. Mastermind or workhorse in arthritis? , 1997, Arthritis and rheumatism.

[3]  Karl Erich Wolff,et al.  States, Transitions, and Life Tracks in Temporal Concept Analysis , 2005, Formal Concept Analysis.

[4]  Bernhard Ganter,et al.  Attribute Exploration with Background Knowledge , 1999, Theor. Comput. Sci..

[5]  Javier Esparza,et al.  Model Checking Using Net Unfoldings , 1993, Sci. Comput. Program..

[6]  Michael Thielscher,et al.  Under Consideration for Publication in Theory and Practice of Logic Programming Flux: a Logic Programming Method for Reasoning Agents , 2003 .

[7]  Y. Okada 8 – Proteinases and Matrix Degradation , 2013 .

[8]  Peter Øhrstrøm,et al.  Time and Logic: A.N. Prior's Formal Analysis of Temporal Concepts , 2009, ICFCA.

[9]  Aviv Regev,et al.  The π-calculus as an Abstraction for Biomolecular Systems , 2004 .

[10]  Markus F. Neurath,et al.  Cytokines in inflammatory bowel disease , 2014, Nature Reviews Immunology.

[11]  H. Kawachi,et al.  Transcription factor Ets-1 is essential for mesangial matrix remodeling. , 2006, Kidney international.

[12]  S. Ross,et al.  How the Smads regulate transcription. , 2008, The international journal of biochemistry & cell biology.

[13]  F. Emmrich,et al.  2nd International meeting on synovium cell biology, physiology and pathology. Canterbury, United Kingdom, 21-23 September 1994. Proceedings and abstracts. , 1995, Annals of the rheumatic diseases.

[14]  R. Gay,et al.  Synovial fibroblasts: key players in rheumatoid arthritis. , 2006, Rheumatology.

[15]  A. Manning,et al.  AP-1 and NF-kappaB regulation in rheumatoid arthritis and murine collagen-induced arthritis. , 1998, Autoimmunity.

[16]  Jeffrey D. Ullman,et al.  Introduction to Automata Theory, Languages and Computation , 1979 .

[17]  Steffen Klamt,et al.  A methodology for the structural and functional analysis of signaling and regulatory networks , 2006, BMC Bioinformatics.

[18]  Michael Karin,et al.  Regulation and Function of IKK and IKK-Related Kinases , 2006, Science's STKE.

[19]  Karl Erich Wolff Interpretation of Automata in Temporal Concept Analysis , 2002, ICCS.

[20]  Hartmut von Hentig Magier oder Magister? : über die Einheit der Wissenschaft im Verständigungsprozeß , 1972 .

[21]  M. Liang,et al.  The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis. , 1988, Arthritis and rheumatism.

[22]  J. H. Ward Hierarchical Grouping to Optimize an Objective Function , 1963 .

[23]  Bernhard Ganter,et al.  Constructing a Knowledge Base for Gene Regulatory Dynamics by Formal Concept Analysis Methods , 2008, AB.

[24]  G. Firestein,et al.  Pathogenesis of rheumatoid arthritis: the role of synoviocytes. , 2001, Rheumatic diseases clinics of North America.

[25]  Y. Shaul,et al.  c-Fos antagonizes the junD gene positive autoregulatory loop; a novel c-Fos role in promoter switching. , 1998, Gene.

[26]  Yubo Sun,et al.  Basic Calcium Phosphate Crystals Induce Matrix Metalloproteinase-1 through the Ras/Mitogen-activated Protein Kinase/c-Fos/AP-1/Metalloproteinase 1 Pathway , 2002, The Journal of Biological Chemistry.

[27]  A. Eisen,et al.  The collagen substrate specificity of human skin fibroblast collagenase. , 1981, The Journal of biological chemistry.

[28]  Bernhard Ganter,et al.  A Formal Concept Analysis Approach to Rough Data Tables , 2011, Trans. Rough Sets.

[29]  Frank Emmrich,et al.  Isolation and characterization of rheumatoid arthritis synovial fibroblasts from primary culture — primary culture cells markedly differ from fourth-passage cells , 2000, Arthritis research.

[30]  D. Eyre,et al.  Sites of stromelysin cleavage in collagen types II, IX, X, and XI of cartilage. , 1991, The Journal of biological chemistry.

[31]  John L. Pfaltz,et al.  Closed Set Mining of Biological Data , 2002, BIOKDD.

[32]  F. Verrecchia,et al.  Transforming Growth Factor-β Signaling Through the Smad Pathway: Role in Extracellular Matrix Gene Expression and Regulation , 2002 .

[33]  Reinhard Guthke,et al.  Adapted Boolean network models for extracellular matrix formation , 2009, BMC Systems Biology.

[34]  Terence P. Speed,et al.  A comparison of normalization methods for high density oligonucleotide array data based on variance and bias , 2003, Bioinform..

[35]  H. D. Jong,et al.  Qualitative simulation of the initiation of sporulation in Bacillus subtilis , 2004, Bulletin of mathematical biology.

[36]  H. Katai,et al.  Human fibroblasts synthesize elevated levels of extracellular matrix proteins in response to interleukin 4. , 1992, The Journal of clinical investigation.

[37]  C. Brinckerhoff,et al.  Two activator protein-1 elements in the matrix metalloproteinase-1 promoter have different effects on transcription and bind Jun D, c-Fos, and Fra-2. , 1995, Matrix biology : journal of the International Society for Matrix Biology.

[38]  Eleftherios T. Papoutsakis,et al.  DNA Array-Based Transcriptional Analysis of Asporogenous, Nonsolventogenic Clostridium acetobutylicum Strains SKO1 and M5 , 2003, Journal of bacteriology.

[39]  Amedeo Napoli,et al.  A Proposal for Combining Formal Concept Analysis and Description Logics for Mining Relational Data , 2007, ICFCA.

[40]  P. Lambert,et al.  The nfkb1 promoter is controlled by proteins of the Ets family. , 1997, Molecular biology of the cell.

[41]  Annett Skupin,et al.  Transcriptional activation of the type I collagen genes COL1A1 and COL1A2 in fibroblasts by interleukin‐4: Analysis of the functional collagen promoter sequences , 2004, Journal of cellular physiology.

[42]  R. Laubenbacher,et al.  Discretization of Time Course Data , 2006 .

[43]  A. Atfi,et al.  Tumor Necrosis Factor-α Inhibits Transforming Growth Factor-β /Smad Signaling in Human Dermal Fibroblasts via AP-1 Activation* , 2000, The Journal of Biological Chemistry.

[44]  Bernhard Ganter,et al.  Formal Concept Analysis: Mathematical Foundations , 1998 .

[45]  Carsten Lutz,et al.  Temporalising Tractable Description Logics , 2007, 14th International Symposium on Temporal Representation and Reasoning (TIME'07).

[46]  M. Yaniv,et al.  Characterization of junD: a new member of the jun proto‐oncogene family. , 1989, The EMBO journal.

[47]  L. March,et al.  Differential regulation of matrix metalloproteinase 2 and matrix metalloproteinase 9 by activated protein C: relevance to inflammation in rheumatoid arthritis. , 2007, Arthritis and rheumatism.

[48]  Sergei O. Kuznetsov,et al.  Recognizing Pseudo-intents is coNP-complete , 2010, CLA.

[49]  Bernhard Ganter Contextual Attribute Logic of Many-Valued Attributes , 2005, Formal Concept Analysis.

[50]  Sergei O. Kuznetsov,et al.  Counting Pseudo-intents and #P-completeness , 2006, ICFCA.

[51]  R. Laubenbacher,et al.  A computational algebra approach to the reverse engineering of gene regulatory networks. , 2003, Journal of theoretical biology.

[52]  M. Feldmann,et al.  Cytokines and anti-cytokine biologicals in autoimmunity: present and future. , 2002, Cytokine & growth factor reviews.

[53]  M. Karin,et al.  The role of Jun, Fos and the AP-1 complex in cell-proliferation and transformation. , 1991, Biochimica et biophysica acta.

[54]  Felix Distel,et al.  Exploring Finite Models in the Description Logic ELgfp , 2009 .

[55]  C. Peirce How to Make Our Ideas Clear , 2011, The Nature of Truth.

[56]  T. Latifi,et al.  Fibroblast growth factor receptor signaling activates the human interstitial collagenase promoter via the bipartite Ets-AP1 element. , 1997, Molecular endocrinology.

[57]  Jean-Pierre Mazat,et al.  Mitochondrial threshold effects. , 2003, The Biochemical journal.

[58]  P. Green,et al.  Multiple facets of junD gene expression are atypical among AP-1 family members , 2008, Oncogene.

[59]  J. Rossert,et al.  Regulation of type I collagen genes expression. , 2000, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.

[60]  Ross D. King,et al.  On the use of qualitative reasoning to simulate and identify metabolic pathway , 2005, Bioinform..

[61]  C. Brinckerhoff,et al.  Transforming growth factor beta inhibitory element in the rabbit matrix metalloproteinase-1 (collagenase-1) gene functions as a repressor of constitutive transcription. , 2000, Biochimica et biophysica acta.

[62]  Gwenael Kervizic,et al.  Dynamical modeling of the cholesterol regulatory pathway with Boolean networks , 2008, BMC Systems Biology.

[63]  Richard Banks,et al.  Qualitatively modelling and analysing genetic regulatory networks: a Petri net approach , 2007, Bioinform..

[64]  Karl Erich Wolff States of Distributed Objects in Conceptual Semantic Systems , 2005, ICCS.

[65]  Karl M Stuhlmeier Mepacrine inhibits matrix metalloproteinases-1 (MMP-1) and MMP-9 activation in human fibroblast-like synoviocytes. , 2003, The Journal of rheumatology.

[66]  A. Ladd,et al.  In situ hybridization studies of stromelysin and collagenase messenger RNA expression in rheumatoid synovium. , 1991, Arthritis and rheumatism.

[67]  S S McCachren,et al.  Expression of metalloproteinases and metalloproteinase inhibitor in human arthritic synovium. , 1991, Arthritis and rheumatism.

[68]  Gerd Stumme,et al.  Formal Concept Analysis: foundations and applications , 2005 .

[69]  F Verrecchia,et al.  Tumor necrosis factor-alpha inhibits transforming growth factor-beta /Smad signaling in human dermal fibroblasts via AP-1 activation. , 2000, The Journal of biological chemistry.

[70]  F. Oakley,et al.  Nuclear factor-kappaB1: regulation and function. , 2008, The international journal of biochemistry & cell biology.

[71]  G. Firestein,et al.  Signal transduction and transcription factors in rheumatic disease. , 1999, Arthritis and rheumatism.

[72]  Sebastian Rudolph,et al.  Formal Concept Analysis Methods for Dynamic Conceptual Graphs , 2001, ICCS.

[73]  G. Firestein,et al.  Gene expression (collagenase, tissue inhibitor of metalloproteinases, complement, and HLA-DR) in rheumatoid arthritis and osteoarthritis synovium. Quantitative analysis and effect of intraarticular corticosteroids. , 1991, Arthritis and rheumatism.

[74]  Vincent Bours,et al.  Cloning of a mitogen-inducible gene encoding a κB DNA-binding protein with homology to the rel oncogene and to cell-cycle motifs , 1990, Nature.

[75]  Michael Hecker,et al.  Gene regulatory network inference: Data integration in dynamic models - A review , 2009, Biosyst..

[76]  Sebastian Rudolph,et al.  Relational exploration: combining description logics and formal concept analysis for knowledge specification , 2006 .

[77]  S. Kauffman Metabolic stability and epigenesis in randomly constructed genetic nets. , 1969, Journal of theoretical biology.

[78]  G. Godeau,et al.  Effects of a vegetable extract from Lupinus albus (LU105) on the production of matrix metalloproteinases (MMP1, MMP2, MMP9) and tissue inhibitor of metalloproteinases (TIMP1, TIMP2) by human gingival fibroblasts in culture , 2003, Clinical Oral Investigations.

[79]  Johannes Wollbold Attribute Exploration of Discrete Temporal Transitions , 2007, ArXiv.

[80]  Ramón Fuentes-González,et al.  L-Fuzzy Concepts and Linguistic Variables in Knowledge Acquisition Processes , 2010, CLA.

[81]  Carsten Peterson,et al.  Random Boolean network models and the yeast transcriptional network , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[82]  Vincent Danos,et al.  Modeling and querying biomolecular interaction networks , 2004, Theor. Comput. Sci..

[83]  Franz Baader,et al.  A Finite Basis for the Set of EL-Implications Holding in a Finite Model , 2008, ICFCA.

[84]  Alvis Brazma,et al.  Current approaches to gene regulatory network modelling , 2007, BMC Bioinformatics.

[85]  Paul J. Higgins,et al.  Transcription Factors , 2010, Methods in Molecular Biology.

[86]  C. Ritchlin,et al.  Fibroblast biology: Effector signals released by the synovial fibroblast in arthritis , 2000, Arthritis research.

[87]  Michael J. Green,et al.  Established rheumatoid arthritis. , 1999, Bailliere's best practice & research. Clinical rheumatology.

[88]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[89]  Amedeo Napoli,et al.  Mining gene expression data with pattern structures in formal concept analysis , 2011, Inf. Sci..

[90]  M. Pillinger,et al.  The role of the synovial fibroblast in rheumatoid arthritis: cartilage destruction and the regulation of matrix metalloproteinases. , 2006, Bulletin of the NYU hospital for joint diseases.

[91]  Susanne Motameny,et al.  Formal Concept Analysis for the Identification of Combinatorial Biomarkers in Breast Cancer , 2008, ICFCA.

[92]  J. A. Hartigan,et al.  A k-means clustering algorithm , 1979 .

[93]  M. Vincenti,et al.  Integration of the NF-kappaB and mitogen-activated protein kinase/AP-1 pathways at the collagenase-1 promoter: divergence of IL-1 and TNF-dependent signal transduction in rabbit primary synovial fibroblasts. , 2000, Cytokine.

[94]  P. Burmeister Formal concept analysis with ConImp : introduction to the basic features , 2003 .

[95]  R. Gay,et al.  Molecular and cellular basis of rheumatoid joint destruction. , 2006, Immunology letters.

[96]  R. Moskowitz,et al.  Development of criteria for the classification and reporting of osteoarthritis. Classification of osteoarthritis of the knee. Diagnostic and Therapeutic Criteria Committee of the American Rheumatism Association. , 1986, Arthritis and rheumatism.

[97]  R. Wait,et al.  Peptidylarginine deiminase from Porphyromonas gingivalis citrullinates human fibrinogen and α-enolase: implications for autoimmunity in rheumatoid arthritis. , 2010, Arthritis and rheumatism.

[98]  J. O'dell,et al.  Therapeutic strategies for rheumatoid arthritis. , 2004, The New England journal of medicine.

[99]  Christopher T. Workman,et al.  DASS: efficient discovery and p-value calculation of substructures in unordered data , 2007, Bioinform..

[100]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.

[101]  Jean-Loup Faulon,et al.  Boolean dynamics of genetic regulatory networks inferred from microarray time series data , 2007, Bioinform..

[102]  T. Sumida,et al.  Direct evidence of high DNA binding activity of transcription factor AP-1 in rheumatoid arthritis synovium. , 1997, Arthritis and rheumatism.

[103]  Franz Baader,et al.  Usability Issues in Description Logic Knowledge Base Completion , 2009, ICFCA.

[104]  Stuart A. Kauffman,et al.  The origins of order , 1993 .

[105]  StummeGerd,et al.  Computing iceberg concept lattices with TITANIC , 2002 .