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This book constitutes the refereed proceedings of the 22nd International Conference on Computational Methods in Systems Biology, CMSB 2024, which took place in Pisa, Italy, during September 16-18, 2024. The 11 full papers included in this book were carefully reviewed and selected from 23 submissions. They deal with computational methods and tools in systems and synthetic biology and their applications, focusing on topics such as modeling and simulation; high-performance methods for computational systems biology; identification of biological systems; applications of machine learning; network modeling, analysis, and inference; automated parameter and model synthesis; model integration and biological databases; multiscale modeling and analysis methods; design, analysis, and verification methods for synthetic biology; methods for biomolecular computing and engineered molecular devices; data-based approaches for systems and synthetic biology; optimality and control of biological systems; modeling, analysis, and control of microbial communities. The conference welcomes new theoretical results with potential applications to systems and synthetic biology, as well as novel applications and case studies of existing methods, tools, or frameworks.

This book constitutes the refereed proceedings of the 21st International Conference on Computational Methods in Systems Biology, CMSB 2023, held in Luxembourg City, Luxembourg, during September 13–15, 2023. The 14 full papers and 3 tool papers presented in this book were carefully reviewed and selected from 28 submissions. CMSB focuses on modeling, simulation, analysis, design and control of biological systems and covers the broad field of computational methods and tools in systems and synthetic biology and their applications.

This book presents novel statistics methods and reproducible software that helps to solve challenging problems in biomedicine. Specifically, it consists of a collection of 11 chapters contributed by some of the leading experts in the mathematical and statistical field which address new challenges in very disparate biomedical areas, such as genomics, cancer, circadian biology, microbiome, mental disorders, and more. The mathematical rigor is written in a user-friendly way to serve a general biomedical audience ranging from trainees or students to doctors, as well as scientific researchers, university departments, and PhD students.

This book discusses computational methods related to biological models using mathematical tools and techniques. The book chapters concentrate on numerical and analytical techniques that provide a global solution for biological models while keeping long-term benefits in mind. The solutions are useful in closely understanding biological models, and the results will be very useful for mathematicians, engineers, doctors, scientists and researchers working on real-life biological models. This book provides significant and current knowledge of biological models related to real-life applications. The book covers both methods and applications.

This book constitutes the refereed proceedings of the 20th International Conference on Computational Methods in Systems Biology, CMSB 2022, held in Bucharest, Romania, in September 2022.The 13 full papers and 4 tool papers were carefully reviewed and selected from 43 submissions. CMSB focuses on modeling, simulation, analysis, design and control of biological systems. The papers are arranged thematically as follows: Chemical reaction networks; Boolean networks; continuous and hybrid models; machine learning; software.

This edited volume discusses the application of very diverse human organotypic models in major areas of biomedical research. The authors lay a main focus on infectious diseases, cancer, allergies, as well as drug/vaccine discovery and toxicology studies. Representing a valid alternative to laboratory animals, these models are relevant for most areas of translational research. As the contemporary research shows, many human tissues can today be cultivated in vitro and used for several research objectives. This book provides an unprecedented overview of recent developments in an exciting field of research methodology. It is a reference guide for scientists in both academia and industry. Readers can update their knowledge and get hands-on recommendations on how to set up an organotypic model in their lab. Chapters'Progress on Reconstructed Human Skin Models for Allergy Research and Identifying Contact Sensitizers'and'Human Organotypic Models for Anti-infective Research'of this book are available open access under a CC BY 4.0 license at link.springer.com.

This book provides an authoritative introduction to the rapidly growing field of chemical reaction network theory. In particular, the book presents deep and surprising theorems that relate the graphical and algebraic structure of a reaction network to qualitative properties of the intricate system of nonlinear differential equations that the network induces. Over the course of three main parts, Feinberg provides a gradual transition from a tutorial on the basics of reaction network theory, to a survey of some of its principal theorems, and, finally, to a discussion of the theory's more technical aspects. Written with great clarity, this book will be of value to mathematicians and to mathematically-inclined biologists, chemists, physicists, and engineers who want to contribute to chemical reaction network theory or make use of its powerful results.

The book uses an integrated approach to predict the behavior of various biological interactions. It further discusses how synthetic biology gathers the information about various systems, in order to either devise an entirely new system, or, to modulate existing systems. The book also tackles the concept of modularity, where biological systems are visualized in terms of their parts.The chapters discuss how the principles of engineering are being used in biomedical sciences, to design biological circuits that can harbor multiple inputs and generate multiple outputs; to create genetic networks and control gene activity, in order to generate a desired response. The book aims to help the readers develop an array of biological parts, and to use these parts to develop synthetic circuits that can be assembled like electronic circuits. The ultimate aim of the book will be to serve as an amalgamation of key ideas of how judiciously synthetic biology could be exploited in therapeutic device and delivery mechanism.

Accelerated Path to Cures provides a transformative perspective on the power of combining advanced computational technologies, modeling, bioinformatics and machine learning approaches with nonclinical and clinical experimentation to accelerate drug development. This book discusses the application of advanced modeling technologies, from target identification and validation to nonclinical studies in animals to Phase 1-3 human clinical trials and post-approval monitoring, as alternative models of drug development. As a case of successful integration of computational modeling and drug development, we discuss the development of oral small molecule therapeutics for inflammatory bowel disease, from the application of docking studies to screening new chemical entities to the development of next-generation in silico human clinical trials from large-scale clinical data. Additionally, this book illustrates how modeling techniques, machine learning, and informatics can be utilized effectively at each stage of drug development to advance the progress towards predictive, preventive, personalized, precision medicine, and thus provide a successful framework for Path to Cures.

This book contributes to better understand how lifestyle modulations can effectively halt the emergence and progression of human diseases. The book will allow the reader to gain a better understanding of the mechanisms by which the environment interferes with the bio-molecular regulatory processes underlying the emergence and progression of complex diseases, such as cancer. Focusing on key and early cellular bio-molecular events giving rise to the emergence of degenerative chronic disease, it builds on previous experience on the development of multi-cellular organisms, to propose a mathematical and computer based framework that allows the reader to analyze the complex interplay between bio-molecular processes and the (micro)-environment from an integrative, mechanistic, quantitative and dynamical perspective. Taking the wealth of empirical evidence that exists it will show how to build and analyze models of core regulatory networks involved in the emergence and progressionof chronic degenerative diseases, using a bottom-up approach.

Many breakthroughs in experimental devices, advanced software, as well as analytical methods for systems biology development have helped shape the way we study DNA, RNA and proteins, on the genomic, transcriptional, translational and posttranslational level. This book highlights the comprehensive topics that encompass systems biology with enormous progress in the development of genome sequencing, proteomic and metabolomic methods in designing and understanding biological systems.Topics covered in this book include fundamentals of modelling networks, circuits and pathways, spatial and multi cellular systems, image-driven systems biology, evolution, noise and decision-making in single cells, systems biology of disease and immunology, and personalized medicine. Special attention is paid to epigenomics, in particular environmental conditions that impact genetic background. The breadth of exciting new data towards discovering fundamental principles and direct applicationof epigenetics in agriculture is also described.The chapter “Deciphering the Universe of RNA Structures and Trans RNA-RNA Interactions of Transcriptomes in vivo - from Experimental Protocols to Computational Analyses” is available open access under a CC BY 4.0 license via link.springer.com.

Fungi are an economic very important class of microbes. Not only do they host a range of versatile enzymes used in industrial applications (biofuels, laundry, food processing), as well do they produce several very important pharmaceutical drugs (statins and penicillins). Moreover, fungal pathogens can cause great damage in agricultural production (Phytophthora and Botrytis) and during mammalian infections (Penicillium marneffei and Candida). Transformation of DNA is used to understand the genetic basis behind these traits. Several different techniques have been developed over the years and readily shown to be decisive methods to improve fungal biotechnology. This book will cover the basics behind the most commonly used transformation methods, as well as associated tools and techniques. Each chapter will provide protocols along with examples to be used in laboratories worldwide.

In this work we plan to revise the main techniques for enumeration algorithms and to show four examples of enumeration algorithms that can be applied to efficiently deal with some biological problems modelled by using biological networks: enumerating central and peripheral nodes of a network, enumerating stories, enumerating paths or cycles, and enumerating bubbles. Notice that the corresponding computational problems we define are of more general interest and our results hold in the case of arbitrary graphs. Enumerating all the most and less central vertices in a network according to their eccentricity is an example of an enumeration problem whose solutions are polynomial and can be listed in polynomial time, very often in linear or almost linear time in practice. Enumerating stories, i.e. all maximal directed acyclic subgraphs of a graph G whose sources and targets belong to a predefined subset of the vertices, is on the other hand an example of an enumeration problem with an exponential number of solutions, that can be solved by using a non trivial brute-force approach. Given a metabolic network, each individual story should explain how some interesting metabolites are derived from some others through a chain of reactions, by keeping all alternative pathways between sources and targets. Enumerating cycles or paths in an undirected graph, such as a protein-protein interaction undirected network, is an example of an enumeration problem in which all the solutions can be listed through an optimal algorithm, i.e. the time required to list all the solutions is dominated by the time to read the graph plus the time required to print all of them. By extending this result to directed graphs, it would be possible to deal more efficiently with feedback loops and signed paths analysis in signed or interaction directed graphs, such as gene regulatory networks. Finally, enumerating mouths or bubbles with a source s in a directed graph, that is enumerating all the two vertex-disjoint directed paths between the source s and all the possible targets, is an example of an enumeration problem in which all the solutions can be listed through a linear delay algorithm, meaning that the delay between any two consecutive solutions is linear, by turning the problem into a constrained cycle enumeration problem. Such patterns, in a de Bruijn graph representation of the reads obtained by sequencing, are related to polymorphisms in DNA- or RNA-seq data.

Together, the volumes in this series present all of the data needed at various length scales for a multidisciplinary approach to modeling and simulation of flows in the cardiovascular and ventilatory systems, especially multiscale modeling and coupled simulations. The cardiovascular and respiratory systems are tightly coupled, as their primary function is to supply oxygen to, and remove carbon dioxide from, the body's cells. Because physiological conduits have deformable and reactive walls, macroscopic flow behavior and prediction must be coupled to nano- and microscopic events in a corrector scheme of regulated mechanism. Therefore, investigation of flows of blood and air in physiological conduits requires an understanding of the biology, chemistry, and physics of these systems, together with the mathematical tools to describe their functioning in quantitative terms. The present volume focuses on macroscopic aspects of the cardiovascular and respiratory systems in normal conditions, i.e., anatomy and physiology, as well as the acquisition and processing of medical images and physiological signals.

Understanding the genetic architecture underlying complex multigene disorders is one of the major goals of human genetics in the upcoming decades. Advances in whole genome sequencing and the success of high throughput functional genomics allow supplementing conventional reductionist biology with systems-level approaches to human heredity and health as systems of interacting genetic, epigenetic, and environmental factors. This integrative approach holds the promise of unveiling yet unexplored levels of molecular organization and biological complexity. It may also hold the key to deciphering the multigene patterns of disease inheritance.

This book deals with the modeling, analysis and simulation of problems arising in the life sciences, and especially in biological processes. The models and findings presented result from intensive discussions with microbiologists, doctors and medical staff, physicists, chemists and industrial engineers and are based on experimental data. They lead to a new class of degenerate density-dependent nonlinear reaction-diffusion convective equations that simultaneously comprise two kinds of degeneracy: porous-medium and fast-diffusion type degeneracy. To date, this class is still not clearly understood in the mathematical literature and thus especially interesting. The author both derives realistic life science models and their above-mentioned governing equations of the degenerate types and systematically studies these classes of equations. In each concrete case well-posedness, the dependence of solutions on boundary conditions reflecting some properties of the environment, and the large-time behavior of solutions are investigated and in some instances also studied numerically.

The rapid progress of neuroscience in the last decade can be largely attributed to significant advances in neuroethology, a branch of science that seeks to understand the neural basis of natural animal behavior. Novel approaches including molecular biological techniques, optical recording methods, functional anatomy, and informatics have brought drastic changes in how the neural systems underlying high-level behaviors such as learning and memory are described. This book introduces recent research techniques in neuroethology, with diverse topics involving nematodes, insects, and vertebrates (birds, mice and primates), divided into sections by research method. Each section consists of two chapters written by different authors who have developed their own unique approaches. Reports of research in “model animals” including C. elegans, Drosophila, and mice, which were not typical specimens in conventional neuroethology, have been deliberately selected for this book because a molecular genetic approach to these animals is necessary for advances in neuroethology. Novel methodology including optical recording and functional labeling with reporter genes such as GFP has been actively used in recent neurobiological studies, and genetic manipulation techniques such as optogenetics also are powerful tools for understanding the molecular basis of neural systems for animal behavior. This book provides not only these new strategies but also thought-provoking statements of philosophy in neuroethology for students and young researchers in the biological sciences.

Computational biology, mathematical biology, biology and biomedicine are currently undergoing spectacular progresses due to a synergy between technological advances and inputs from physics, chemistry, mathematics, statistics and computer science. The goal of this book is to evidence this synergy by describing selected developments in the following fields: bioinformatics, biomedicine and neuroscience. This work is unique in two respects - first, by the variety and scales of systems studied and second, by its presentation: Each chapter provides the biological or medical context, follows up with mathematical or algorithmic developments triggered by a specific problem and concludes with one or two success stories, namely new insights gained thanks to these methodological developments. It also highlights some unsolved and outstanding theoretical questions, with a potentially high impact on these disciplines. Two communities will be particularly interested in this book. The first one is the vast community of applied mathematicians and computer scientists, whose interests should be captured by the added value generated by the application of advanced concepts and algorithms to challenging biological or medical problems. The second is the equally vast community of biologists. Whether scientists or engineers, they will find in this book a clear and self-contained account of concepts and techniques from mathematics and computer science, together with success stories on their favorite systems. The variety of systems described represents a panoply of complementary conceptual tools. On a practical level, the resources listed at the end of each chapter (databases, software) offer invaluable support for getting started on a specific topic in the fields of biomedicine, bioinformatics and neuroscience.

The book presents topics in discrete biomathematics. Mathematics has been widely used in modeling biological phenomena. However, the molecular and discrete nature of basic life processes suggests that their logic follow principles that are intrinsically based on discrete and informational mechanisms. The ultimate reason of polymers, as key element of life, is directly based on the computational power of strings, and the intrinsic necessity of metabolism is related to the mathematical notion of multiset. The switch of the two roots of bioinformatics suggests a change of perspective. In bioinformatics, the biologists ask computer scientists to assist them in processing biological data. Conversely, in infobiotics mathematicians and computer scientists investigate principles and theories yielding new interpretation keys of biological phenomena. Life is too important to be investigated by biologists alone, and though computers are essential to process data from biological laboratories, many fundamental questions about life can be appropriately answered by a perspicacious intervention of mathematicians, computer scientists, and physicists, who will complement the work of chemists, biochemists, biologists, and medical investigators. The volume is organized in seven chapters. The first part is devoted to research topics (Discrete information and life, Strings and genomes, Algorithms and Biorhythms, Life Strategies), the second one to mathematical backgrounds (Numbers and Measures, Languages and Grammars, Combinations and Chances).

Metastatic dissemination of cancer is a main cause of cancer related deaths, therefore biological mechanisms implicated in metastatic process presents an essential object of cancer research. This research requires creation and utilization of adequate laboratory models. The book describes main approaches to model processes of metastatic cancer dissemination and metastases development. The book is structured in according with various metastatic pathways reflecting molecular specificity of metastatic process as well as anatomical specificity of aria of dissemination. Each chapter is introduced by short discussion of clinical aspects of certain metastatic pathway. Especial attention is paid for methods of visualization, quantification and analysis of the modeled metastases. Additional chapter is devoted to methods of mathematic modeling of tumor spread. The data presented in the book may be helpful for cancer researchers and oncologists.

Immuno Systems Biology aims to study the immune system in the more integrated manner on how cells and molecules participate at different system levels to the immune function. Through this book Kumar Selvarajoo introduces to physicists, chemists, computer scientists, biologists and immunologists the idea of an integrated approach to the understanding of mammalian immune system. Geared towards a researcher with limited immunological and computational analytical experience, the book provides a broad overview to the subject and some instruction in basic computational, theoretical and experimental approaches. The book links complex immunological processes with computational analysis and emphasizes the importance of immunology to the mammalian system.

The volumes in this authoritative series present a multidisciplinary approach to modeling and simulation of flows in the cardiovascular and ventilatory systems, especially multiscale modeling and coupled simulations. The cardiovascular and respiratory systems are tightly coupled, as their primary function is to supply oxygen to and remove carbon dioxide from the body's cells. Because physiological conduits have deformable and reactive walls, macroscopic flow behavior and prediction must be coupled to phenomenological models of nano- and microscopic events in a corrector scheme of regulated mechanisms when the vessel lumen caliber varies markedly. Therefore, investigation of flows of blood and air in physiological conduits requires an understanding of the biology, chemistry, and physics of these systems together with the mathematical tools to describe their functioning. Volume 4 is devoted to major sets of intracellular mediators that transmit signals upon stimulation of cell-surface receptors. Activation of signaling effectors triggers the release of substances stored in cellular organelles and/or gene transcription and protein synthesis. Complex stages of cell signaling can be studied using proper mathematical models, once the role of each component is carefully handled. Volume 4 also reviews various categories of cytosolic and/or nuclear mediators and illustrates some major signal transduction pathways, such as NFkappaB axis, oxygen sensing, and mechanotransduction.

Biosimulation is an approach to biomedical research and the treatment of patients in which computer modeling goes hand in hand with experimental and clinical work. Constructed models are used to interpret experimental results and to accumulate information from experiment to experiment.This book explains the concepts used in the modeling of biological phenomena and goes on to present a series of well-documented models of the regulation of various genetic, cellular and physiological processes. The way how the use of computer models allows optimization of cancer treatment for individual patients is discussed and models of interacting nerve cells that can be used to design new treatments for patients with Parkinson's disease are explained. Furthermore this volume provides an overview on the use of models in industry, and presents the view of regulatory agencies on the topic.

This book is intended as a communication platform to bridge the cultural, conceptual, and technological gap among the key systems biology disciplines of biology, mathematics, and information technology. To support this goal, contributors were asked to adopts an approach that appeals to audiences from different backgrounds.

BetaSys uses the example of regulated exocytosis in pancreatic β-cells, and its relevance to diabetes, to illustrate the major concepts of systems biology, its methods and applications.

System Biology encompasses the knowledge from diverse fields such as Molecular Biology, Immunology, Genetics, Computational Biology, Mathematical Biology, etc. not only to address key questions that are not answerable by individual fields alone, but also to help in our understanding of the complexities of biological systems. Whole genome expression studies have provided us the means of studying the expression of thousands of genes under a particular condition and this technique had been widely used to find out the role of key macromolecules that are involved in biological signaling pathways. However, making sense of the underlying complexity is only possible if we interconnect various signaling pathways into human and computer readable network maps. These maps can then be used to classify and study individual components involved in a particular phenomenon. Apart from transcriptomics, several individual gene studies have resulted in adding to our knowledge of key components that are involved in a signaling pathway. It therefore becomes imperative to take into account of these studies also, while constructing our network maps to highlight the interconnectedness of the entire signaling pathways and the role of that particular individual protein in the pathway. This collection of articles will contain a collection of pioneering work done by scientists working in regulatory signaling networks and the use of large scale gene expression and omics data. The distinctive features of this book would be: Act a single source of information to understand the various components of different signaling network (roadmap of biochemical pathways, the nature of a molecule of interest in a particular pathway, etc.), Serve as a platform to highlight the key findings in this highly volatile and evolving field, and Provide answers to various techniques both related to microarray and cell signaling to the readers.

Mathematical Biology has grown at an astonishing rate and has established itself as a distinct discipline. Mathematical modeling is now being applied in every major discipline in the biological sciences. Though the field has become increasingly large and specialized, this book remains important as a text that introduces some of the exciting problems which arise in the biological sciences and gives some indication of the wide spectrum of questions that modeling can address.

Mathematical models in biology and medicine cannot be based on natural laws as it is the case with physics and chemistry. This is due to the fact that biological and medical processes are concerned with living organisms. Mathematical models, however, can be used as a language by which certain aspects of biological or medical processes can be expressed. In general, several mathematical models can be designed in order to describe a biological or medical process and there is no unique criterion which model gives the best description. This book presents several of these models and shows applications of them to different biological and medical problems. The book shows that operations research expertise is necessary in respect to modeling, analysis and optimization of biosystems.

The first of a two-volume set, this book constitutes the refereed proceedings of the Second International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2007, held in La Manga del Mar Menor, Spain in June 2007. It includes all the contributions mainly related with theoretical, conceptual and methodological aspects linking AI and knowledge engineering with neurophysiology, clinics and cognition.

Mathematicalmodelingofhumanphysiopathologyisatremendouslyambitioustask. It encompasses the modeling of most diverse compartments such as the cardiovas- lar,respiratory,skeletalandnervoussystems,aswellasthemechanicalandbioch- ical interaction between blood?ow and arterial walls, and electrocardiac processes and electric conduction in biological tissues. Mathematical models can be set up to simulate both vasculogenesis (the aggregation and organization of endothelial cells dispersed in a given environment) and angiogenesis (the formation of new vessels sprouting from an existing vessel) that are relevant to the formation of vascular networks, and in particular to the description of tumor growth. The integration of models aimed at simulating the cooperation and interrelation of different systems is an even more dif?cult task. It calls for the setting up of, for instance, interaction models for the integrated cardio-vascular system and the interplay between the central circulation and peripheral compartments, models for the mid-to-long range cardiovascular adjustments to pathological conditions (e.g., to account for surgical interventions, congenital malformations, or tumor growth), models for integration among circulation, tissue perfusion, biochemical and thermal regulation, models for parameter identi?cation and sensitivity analysis to parameter changes or data uncertainty – and many others.

On April 26-28, 2001, the Board on Mathematical Sciences and Their Applications (BMSA) and the Board on Life Sciences of the National Research Council cosponsored a workshop on the dynamical modeling of complex biomedical systems. The workshop's goal was to identify some open research questions in the mathematical sciences whose solution would contribute to important unsolved problems in three general areas of the biomedical sciences: disease states, cellular processes, and neuroscience. The workshop drew a diverse group of over 80 researchers, who engaged in lively discussions. To convey the workshop's excitement more broadly, and to help more mathematical scientists become familiar with these very fertile interface areas, the BMSA appointed one of its members, George Casella, of the University of Florida, as rapporteur. He developed this summary with the help of two colleagues from his university, Rongling Wu and Sam S. Wu, assisted by Scott Weidman, BMSA director. This summary represents the viewpoint of its authors only and should not be taken as a consensus report of the BMSA or of the National Research Council.