09091 Abstracts Collection -- Formal Methods in Molecular Biology

From 23. February to 27. February 2009, the Dagstuhl Seminar 09091 ``Formal Methods in Molecular Biology \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

A Study of the PDGF Signaling Pathway with PRISM

In this paper, we apply the probabilistic model checker PRISM to the analysis of a biological system -- the Platelet-Derived Growth Factor (PDGF) signaling pathway, demonstrating in detail how this pathway can be analyzed in PRISM. We show that quantitative verification can yield a better understanding of the PDGF signaling pathway.Comment: In Proceedings CompMod 2011, arXiv:1109.104

Computational Modeling of Complex Protein Activity Networks

Because of the numerous entities interacting, the complexity of the networks that regulate cell fate makes it impossible to analyze and understand them using the human brain alone. Computational modeling is a powerful method to unravel complex systems. We recently described the development of a user-friendly computational tool, Analysis of Networks with Interactive MOdeling (ANIMO). ANIMO is a powerful tool to formalize knowledge on molecular interactions. This formalization entails giving a precise mathematical (formal) description of molecular states and of interactions between molecules. Such a model can be simulated, thereby in silico mimicking the processes that take place in the cell. In sharp contrast to classical graphical representations of molecular interaction networks, formal models allow in silico experiments and functional analysis of the dynamic behavior of the network. In addition, ANIMO was developed specifically for use by biologists who have little or no prior modeling experience. In this chapter, we guide the reader through the ANIMO workflow using osteoarthritis (OA) as a case study. WNT, IL-1β, and BMP signaling and cross talk are used as a concrete and illustrative model

Probabilistic Approximation and Analysis Techniques for Bio-Pathway Models

Ph.DDOCTOR OF PHILOSOPH

Probabilistic verification and analysis of biopathway dynamics

Ph.DDOCTOR OF PHILOSOPH

Multilevel Attributed Probabilistic P System Implementazione e Definizione

1 Introduction 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Published Material . . . . . . . . . . . . . . . . . . . . . . . . 5 2 State of the art 7 3 Background 13 3.1 Denition of multiset and related operations . . . . . . . . . . 13 3.2 Notions of P Systems . . . . . . . . . . . . . . . . . . . . . . . 14 3.2.1 Formal denition of a P Systems . . . . . . . . . . . . 15 3.2.2 Some relevant extensions . . . . . . . . . . . . . . . . . 16 3.2.3 Minimal Probabilistic P systems . . . . . . . . . . . . 18 3.2.4 Attributed Probabilistic P Systems . . . . . . . . . . . 22 4 Multilevel Attributed Probabilistic P Systems 25 4.1 MAPPS formal and informal denition . . . . . . . . . . . . . 26 4.1.1 informal denition . . . . . . . . . . . . . . . . . . . . 26 4.1.2 Formal denition . . . . . . . . . . . . . . . . . . . . . 28 4.2 Semantics, formal denition . . . . . . . . . . . . . . . . . . . 31 4.2.1 notes about termination . . . . . . . . . . . . . . . . . 36 4.3 MAPPS a simple example . . . . . . . . . . . . . . . . . . . . 37 4.4 MAPPS another example: Predator / Prey . . . . . . . . . . 39 4.4.1 Sets . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 4.4.2 Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 4.4.3 Functions . . . . . . . . . . . . . . . . . . . . . . . . . 45 5 APP - General purpose implementation 47 5.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 5.1.1 Programming language used in the project . . . . . . . 47 5.2 Commentary to code . . . . . . . . . . . . . . . . . . . . . . . 48 5.2.1 software engine . . . . . . . . . . . . . . . . . . . . . . 48 5.2.2 input les . . . . . . . . . . . . . . . . . . . . . . . . . 50 5.2.3 apply method . . . . . . . . . . . . . . . . . . . . . . . 52 7 5.2.4 Rating method . . . . . . . . . . . . . . . . . . . . . . 53 5.2.5 How we implements the probability - Matrices of choice 54 5.2.6 State updating . . . . . . . . . . . . . . . . . . . . . . 56 6 MAPP - General purpose implementation 59 6.1 Software engine extension . . . . . . . . . . . . . . . . . . . . 59 6.1.1 class Membrane . . . . . . . . . . . . . . . . . . . . . 59 6.1.2 input les . . . . . . . . . . . . . . . . . . . . . . . . . 62 6.1.3 class Membrane implementation . . . . . . . . . . . . 62 6.1.4 Membrane Attributes . . . . . . . . . . . . . . . . . . 63 6.1.5 Updating functions . . . . . . . . . . . . . . . . . . . . 64 6.1.6 Membrane example . . . . . . . . . . . . . . . . . . . . 65 7 A case of study: Serengeti Lions. 67 7.1 Serengeti Lions - informal description . . . . . . . . . . . . . . 69 7.2 Serengeti Lions - Formal denition . . . . . . . . . . . . . . . 71 8 Experimental results 83 8.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 8.2 data and results . . . . . . . . . . . . . . . . . . . . . . . . . . 83 8.2.1 rst results . . . . . . . . . . . . . . . . . . . . . . . . 83 8.3 A step forward . . . . . . . . . . . . . . . . . . . . . . . . . . 89 9 Final Conclusions 93 Bibliography 9

PROTEIN FUNCTION, DIVERISTY AND FUNCTIONAL INTERPLAY

Functional annotations of novel or unknown proteins is one of the central problems in post-genomics bioinformatics research. With the vast expansion of genomic and proteomic data and technologies over the last decade, development of automated function prediction (AFP) methods for large-scale identification of protein function has be-come imperative in many aspects. In this research, we address two important divergences from the “one protein – one function” concept on which all existing AFP methods are developed

Exploring the Effects of Toll-Like Receptor 4 Antagonism on Gastrointestinal Mucositis and Tumour Activity

Gastrointestinal mucositis (GIM) is a hallmark of chemotherapy-induced gastrointestinal toxicity. It affects up to 80% of patients with cancer depending on their treatment regimen. Symptoms of GIM include weight loss, diarrhoea and bleeding. These symptoms can be so severe and debilitating that it often necessitates a reduction of treatment doses or discontinuation of the treatment which compromises patient survival. Unfortunately, there are no effective treatment strategies for these patients and more studies are required to develop potential intervention strategies. TLR4 is an intra- and extra-cellular receptor expressed on endosomes and cytoplasmic membranes. TLR4 recognises pathogen-associated molecular patterns (PAMPs) (flagellin and LPS) and damage-associated molecular patterns (DAMPs) (calprotectin, S100A8/9 HMGB1 and HSP70) through its co-receptors MD-2 and CD-14. The activation of TLR4 has been proposed to have a major influence on inflammatory signalling pathways and the pathogenesis of GIM. Inhibition of TLR4 has been postulated as an effective way to treat intestinal inflammation. However, there is a limited number of studies looking into the potential of TLR4 antagonism as a therapeutic approach for gastrointestinal (GI) inflammation. The work described in this thesis focussed primarily on the influence of TLR4 antagonism on GI toxicity stemming from irinotecan/CPT-11, a DNA topoisomerase I inhibitor used in the treatment of advanced colorectal cancer. The TLR4 antagonists studied were TAK-242 and IAXO-102, due to their potential to serve as alternative treatment options for GIM. Firstly, I modelled binding sites and affinity of IAXO-102, TAK-242 and SN-38 (the active metabolite of CPT-11) to the human TLR4/MD-2 complex, identifying specific amino acid residues of interaction and performed 3D structural analysis through in silico docking analysis. Computational techniques provide the possibility to explore drug development opportunities in order to rapidly provide structural, chemical, and biological data to improve understanding of potential drugs and their targets. The results from this study could contribute to rational development of therapeutic anti-inflammatory drugs targeting TLR4 in the GI tract. Secondly, I assessed the potential of the TAK-242 and IAXO-102 to attenuate GI inflammation in 2 different models; 1) an in vitro model using intestinal epithelial cell lines (T84, HT-29) and monocyte-like cells (U937), and 2) an ex vivo model using segments of mouse colon. Both models were induced with inflammation using TLR4 agonists and inflammatory mediators. Results from this study did not show significant protection with TAK-242 or IAXO-102 which, highlighted the limitation of in vitro and ex vivo models to accurately simulate GIM. Finally, from the in vitro and ex vivo studies, the TLR4 antagonist with the greatest potential for clinical development, IAXO-102 was evaluated for effectiveness to attenuate GI inflammation as well as supress tumour activity in a colorectal-tumour bearing mouse model of CPT-11-induced GIM. Results showed that IAXO-102 was able to prevent diarrhoea in mice treated with CPT-11 as well as reduce tumour volume. However, it had no effect in protecting the colon from tissue damage or changing proliferation and apoptosis rates in both the colon and tumour. As such, it was concluded TLR4 activation plays a partial role in GIM development but further research is required to understand the specific inflammatory signals underpinning tissue-level changes.Thesis (Ph.D.) -- University of Adelaide, School of Biomedicine, 202

High-Fat High-Saturated Diet

Dietary fat quality is a crucial determinant of several physiological, biochemical and molecular processes in the body, tissues and cells. As a source of energy, Fatty Acids (FA) are mainly stored in fat cells and within lipid droplets (LD) in oxidative and steroidogenic tissues, but significant amounts are also found in cell membranes where their structural role is crucial for membrane protein functions and the control of cellular functions. Differential effects have been identified between different types FA on inflammatory and metabolic diseases during obesity or in response to physical exercise and chronic diseases. The most recent dietary guidelines advise that lipids should represent 35% of the daily energy intake in order to prevent deleterious effects of high glycaemic index carbohydrates and deficiency in essential fatty acids. Hence, the prevalence of obesity could rise dramatically despite a fall in total fat intake. Advice is more focused on the improvement of the quality of fat than on the reduction of total fat intake. Dietary fat sources provide a mixture of saturated FA (SFA), monounsaturated FA (MUFA) and polyunsaturated FA (PUFA). Most institutional dietary guidelines claim that the consumption of SFA should be limited to the expense of MUFA and PUFA as a nutritional strategy for the prevention of chronic diseases. The role of dietary SFA and MUFA in cardiometabolic risk remains controversial in the scientific community. This special issue was proposed to publish articles that bring new elements into the topic by collecting recent advances for students and professionals involved in lipid and health

Efecto del tauroursodeoxicolato en la regulación de la neuroinflamación aguda

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Bioquímica. Fecha de lectura: 10-07-201