Computational Methods For Estimating The Kinetic Parameters Of Biological Systems

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Computational Methods for Estimating the Kinetic Parameters of Biological Systems

Author : Quentin Vanhaelen
Publisher :
ISBN 13 : 9781071617670
Total Pages : 379 pages
Book Rating : 4.6/5 (176 download)

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Book Synopsis Computational Methods for Estimating the Kinetic Parameters of Biological Systems by : Quentin Vanhaelen

Download or read book Computational Methods for Estimating the Kinetic Parameters of Biological Systems written by Quentin Vanhaelen and published by . This book was released on 2022 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: This detailed book provides an overview of various classes of computational techniques, including machine learning techniques, commonly used for evaluating kinetic parameters of biological systems. Focusing on three distinct situations, the volume covers the prediction of the kinetics of enzymatic reactions, the prediction of the kinetics of protein-protein or protein-ligand interactions (binding rates, dissociation rates, binding affinities), and the prediction of relatively large set of kinetic rates of reactions usually found in quantitative models of large biological networks. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of expert implementation advice that leads to successful results. Authoritative and practical, Computational Methods for Estimating the Kinetic Parameters of Biological Systems will be of great interest for researchers working through the challenge of identifying the best type of algorithm and who would like to use or develop a computational method for the estimation of kinetic parameters.

Kinetic Modelling in Systems Biology

Author : Oleg Demin
Publisher : CRC Press
ISBN 13 : 1420011669
Total Pages : 360 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Kinetic Modelling in Systems Biology by : Oleg Demin

Download or read book Kinetic Modelling in Systems Biology written by Oleg Demin and published by CRC Press. This book was released on 2008-10-24 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: With more and more interest in how components of biological systems interact, it is important to understand the various aspects of systems biology. Kinetic Modelling in Systems Biology focuses on one of the main pillars in the future development of systems biology. It explores both the methods and applications of kinetic modeling in this emerging f

Numerical Methods for the Life Scientist

Author : Heino Prinz
Publisher : Springer Science & Business Media
ISBN 13 : 3642208207
Total Pages : 155 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Numerical Methods for the Life Scientist by : Heino Prinz

Download or read book Numerical Methods for the Life Scientist written by Heino Prinz and published by Springer Science & Business Media. This book was released on 2011-08-06 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: Enzyme kinetics, binding kinetics and pharmacological dose-response curves are currently analyzed by a few standard methods. Some of these, like Michaelis-Menten enzyme kinetics, use plausible approximations, others, like Hill equations for dose-response curves, are outdated. Calculating realistic reaction schemes requires numerical mathematical routines which usually are not covered in the curricula of life science. This textbook will give a step-by-step introduction to numerical solutions of non-linear and differential equations. It will be accompanied with a set of programs to calculate any reaction scheme on any personal computer. Typical examples from analytical biochemistry and pharmacology can be used as versatile templates. When a reaction scheme is applied for data fitting, the resulting parameters may not be unique. Correlation of parameters will be discussed and simplification strategies will be offered.

A Guide to Numerical Modelling in Systems Biology

Author : Peter Deuflhard
Publisher : Springer
ISBN 13 : 3319200593
Total Pages : 185 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis A Guide to Numerical Modelling in Systems Biology by : Peter Deuflhard

Download or read book A Guide to Numerical Modelling in Systems Biology written by Peter Deuflhard and published by Springer. This book was released on 2015-07-06 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for students of computational systems biology with only a limited background in mathematics. Typical books on systems biology merely mention algorithmic approaches, but without offering a deeper understanding. On the other hand, mathematical books are typically unreadable for computational biologists. The authors of the present book have worked hard to fill this gap. The result is not a book on systems biology, but on computational methods in systems biology. This book originated from courses taught by the authors at Freie Universität Berlin. The guiding idea of the courses was to convey those mathematical insights that are indispensable for systems biology, teaching the necessary mathematical prerequisites by means of many illustrative examples and without any theorems. The three chapters cover the mathematical modelling of biochemical and physiological processes, numerical simulation of the dynamics of biological networks and identification of model parameters by means of comparisons with real data. Throughout the text, the strengths and weaknesses of numerical algorithms with respect to various systems biological issues are discussed. Web addresses for downloading the corresponding software are also included.

Computational Methods in Systems Biology

Author : Monika Heiner
Publisher : Springer
ISBN 13 : 3540885625
Total Pages : 413 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Computational Methods in Systems Biology by : Monika Heiner

Download or read book Computational Methods in Systems Biology written by Monika Heiner and published by Springer. This book was released on 2008-10-05 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Computational Methods in Systems Biology, CMSB 2008, held in Rostock, Germany, in September 2008. The 21 revised full papers presented together with the summaries of 5 invited papers were carefully reviewed and selected from more than 60 submissions. The papers cover theoretical or applied contributions that are motivated by a biological question focusing on modeling approaches, including process algebra, simulation approaches, analysis methods, in particular model checking and flux analysis, and case studies.

Computational Methods in Systems Biology

Author : Roberta Gori
Publisher : Springer Nature
ISBN 13 : 303171671X
Total Pages : 268 pages
Book Rating : 4.0/5 (317 download)

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Book Synopsis Computational Methods in Systems Biology by : Roberta Gori

Download or read book Computational Methods in Systems Biology written by Roberta Gori and published by Springer Nature. This book was released on with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Network Bioscience, 2nd Edition

Author : Marco Pellegrini
Publisher : Frontiers Media SA
ISBN 13 : 288963650X
Total Pages : 270 pages
Book Rating : 4.8/5 (896 download)

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Book Synopsis Network Bioscience, 2nd Edition by : Marco Pellegrini

Download or read book Network Bioscience, 2nd Edition written by Marco Pellegrini and published by Frontiers Media SA. This book was released on 2020-03-27 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network science has accelerated a deep and successful trend in research that influences a range of disciplines like mathematics, graph theory, physics, statistics, data science and computer science (just to name a few) and adapts the relevant techniques and insights to address relevant but disparate social, biological, technological questions. We are now in an era of 'big biological data' supported by cost-effective high-throughput genomic, transcriptomic, proteomic, metabolomic data collection techniques that allow one to take snapshots of the cells' molecular profiles in a systematic fashion. Moreover recently, also phenotypic data, data on diseases, symptoms, patients, etc. are being collected at nation-wide level thus giving us another source of highly related (causal) 'big data'. This wealth of data is usually modeled as networks (aka binary relations, graphs or webs) of interactions, (including protein-protein, metabolic, signaling and transcription-regulatory interactions). The network model is a key view point leading to the uncovering of mesoscale phenomena, thus providing an essential bridge between the observable phenotypes and 'omics' underlying mechanisms. Moreover, network analysis is a powerful 'hypothesis generation' tool guiding the scientific cycle of 'data gathering', 'data interpretation, 'hypothesis generation' and 'hypothesis testing'. A major challenge in contemporary research is the synthesis of deep insights coming from network science with the wealth of data (often noisy, contradictory, incomplete and difficult to replicate) so to answer meaningful biological questions, in a quantifiable way using static and dynamic properties of biological networks.

Assessing Computational Methods and Science Policy in Systems Biology

Author : Andrea Redwing Castillo
Publisher :
ISBN 13 :
Total Pages : 112 pages
Book Rating : 4.:/5 (51 download)

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Book Synopsis Assessing Computational Methods and Science Policy in Systems Biology by : Andrea Redwing Castillo

Download or read book Assessing Computational Methods and Science Policy in Systems Biology written by Andrea Redwing Castillo and published by . This book was released on 2009 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: (cont.) I use mass action theory expressed in kronecker products to exploit the ability to apply numerical methods-including sensitivity analysis via boundary value formulation (BVP) and trapiezoidal integration rule-and experimental techniques-including partial reaction fitting and enzyme-driven activations-when mathematically modeling large-scale biochemical networks. Amidst other applicable methodologies, my approach is grounded in the law of mass action because it is based in experimental data and biomolecular mechanistic properties, yet provides predictive power in the complete delineation of the biological system dynamics for all future time points. The results of my research demonstrate the holistic approach that mass action method-ologies have in determining emergent properties of biological systems. I further stress the necessity to enforce collaboration and standardization in future policymaking, with reconsiderations on current stakeholder incentive to redirect academia and industry focus from new molecular entities to interests in holistic understanding of the complexities and dynamics of life entities. Such redirection away from reductionism could further progress basic and applied scientific research to embetter our circumstances through new treatments and preventive measures for health, and development of new strains and disease control in agriculture and ecology [13].

Computational Methods in Systems Biology

Author : Ezio Bartocci
Publisher : Springer
ISBN 13 : 3319451774
Total Pages : 361 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Computational Methods in Systems Biology by : Ezio Bartocci

Download or read book Computational Methods in Systems Biology written by Ezio Bartocci and published by Springer. This book was released on 2016-09-03 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th International Conference on Computational Methods in Systems Biology, CMSB 2016, held in Cambridge, UK, in September 2016. The 20 full papers, 3 tool papers and 9 posters presented were carefully reviewed and selected from 37 regular paper submissions. The topics include formalisms for modeling biological processes; models and their biological applications; frameworks for model verification, validation, analysis, and simulation of biological systems; high-performance computational systems biology and parallel implementations; model inference from experimental data; model integration from biological databases; multi-scale modeling and analysis methods; and computational approaches for synthetic biology.

Computational Approaches in Drug Discovery, Development and Systems Pharmacology

Author : Rupesh Kumar Gautam
Publisher : Elsevier
ISBN 13 : 0323993737
Total Pages : 364 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Computational Approaches in Drug Discovery, Development and Systems Pharmacology by : Rupesh Kumar Gautam

Download or read book Computational Approaches in Drug Discovery, Development and Systems Pharmacology written by Rupesh Kumar Gautam and published by Elsevier. This book was released on 2023-02-15 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Approaches in Drug Discovery, Development and Systems Pharmacology provides detailed information on the use of computers in advancing pharmacology. Drug discovery and development is an expensive and time-consuming practice, and computer-assisted drug design (CADD) approaches are increasing in popularity in the pharmaceutical industry to accelerate the process. With the help of CADD, scientists can focus on the most capable compounds so that they can minimize the synthetic and biological testing pains. This book examines success stories of CADD in drug discovery, drug development and role of CADD in system pharmacology, additionally including a focus on the role of artificial intelligence (AI) and deep machine learning in pharmacology. Computational Approaches in Drug Discovery, Development and Systems Pharmacology will be useful to researchers and academics working in the area of CADD, pharmacology and Bioinformatics. Explains computer use in pharmacology using real-life case studies Provides information about biological activities using computer technology, thus allowing for the possible reduction of the number of animals used for research Describes the role of AI in pharmacology and applications of CADD in various diseases

Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology

Author : David Holcman
Publisher : Springer
ISBN 13 : 3319626272
Total Pages : 377 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology by : David Holcman

Download or read book Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology written by David Holcman and published by Springer. This book was released on 2017-10-04 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of stochastic reaction-diffusion models, while in the latter, one can describe the processes by adopting the framework of Markov jump processes and stochastic differential equations. Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology will appeal to graduate students and researchers in the fields of applied mathematics, biophysics, and cellular biology.

Mathematical Modeling of Complex Biological Systems

Author : Abdelghani Bellouquid
Publisher : Springer Science & Business Media
ISBN 13 : 0817645039
Total Pages : 194 pages
Book Rating : 4.8/5 (176 download)

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Book Synopsis Mathematical Modeling of Complex Biological Systems by : Abdelghani Bellouquid

Download or read book Mathematical Modeling of Complex Biological Systems written by Abdelghani Bellouquid and published by Springer Science & Business Media. This book was released on 2007-10-10 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the evolution of several socio-biological systems using mathematical kinetic theory. Specifically, it deals with modeling and simulations of biological systems whose dynamics follow the rules of mechanics as well as rules governed by their own ability to organize movement and biological functions. It proposes a new biological model focused on the analysis of competition between cells of an aggressive host and cells of a corresponding immune system. Proposed models are related to the generalized Boltzmann equation. The book may be used for advanced graduate courses and seminars in biological systems modeling.

Towards Automated Reaction Kinetics with Message Passing Neural Networks

Author : Lagnajit Pattanaik
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (139 download)

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Book Synopsis Towards Automated Reaction Kinetics with Message Passing Neural Networks by : Lagnajit Pattanaik

Download or read book Towards Automated Reaction Kinetics with Message Passing Neural Networks written by Lagnajit Pattanaik and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive chemistry holds great promise to accelerate scientific discovery and innovation. An approach towards predictive chemistry involves decomposing systems into kinetic mechanisms consisting of elementary reactions and quantitatively describing each of those reactions. Incredibly, the immense progress in computational methods and compute power now allows the calculation of thermodynamic and kinetic parameters at an accuracy necessary for predictive chemistry. Unfortunately, real systems can consist of tens of thousands of elementary reactions, so it is infeasible to calculate these parameters using traditional, labor-intensive computational methods. This thesis focuses on computing kinetic parameters by both automating and accelerating the computational pipelines used to generate them, relying on modern machine learning frameworks--specifically, message passing neural networks--to facilitate these calculations. Noting that in the framework of automated kinetic parameter calculation, transition state search is a key bottleneck, this thesis first devises a method to generate transition state geometries with deep learning. The new method achieves improvements in both accuracy and speed compared to existing alternatives. This thesis next investigates a fundamental limitation of message passing neural networks to capture tetrahedral chirality and proposes several fixes to address this limitation. While generating a single transition state structure is an important goal, accurate calculation of kinetic parameters often requires investigating multiple conformations. Hence, this thesis builds a generative framework to predict multiple low-energy conformations directly from the molecular graph. The method is demonstrated for stable species conformer generation and outperforms existing baselines. Integrating all the developed models together, this thesis next develops an end-to-end pipeline to generate transition state conformers directly from the atom-mapped reaction SMILES. While most of presented work investigates reactions in the gas phase, reactions in condensed phase require additional solvation corrections. Therefore, this thesis constructs a large dataset of solution free energies across a range of solvents. It then develops a model to predict relevant conformations of the solute for any given solute-solvent pair. The tools developed in this thesis will become an integral part of modern computational chemistry pipelines. Undoubtedly, the future of automated predictive chemistry will heavily rely on these and similar deep learning models for fast and accurate parameter estimation.

Parameter Estimation in Biological Systems

Author : Joel Barry Swartz
Publisher :
ISBN 13 :
Total Pages : 590 pages
Book Rating : 4.:/5 (29 download)

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Book Synopsis Parameter Estimation in Biological Systems by : Joel Barry Swartz

Download or read book Parameter Estimation in Biological Systems written by Joel Barry Swartz and published by . This book was released on 1973 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Statistical Systems Biology

Author : Michael Stumpf
Publisher : John Wiley & Sons
ISBN 13 : 1119952042
Total Pages : 624 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Handbook of Statistical Systems Biology by : Michael Stumpf

Download or read book Handbook of Statistical Systems Biology written by Michael Stumpf and published by John Wiley & Sons. This book was released on 2011-09-09 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems Biology is now entering a mature phase in which the key issues are characterising uncertainty and stochastic effects in mathematical models of biological systems. The area is moving towards a full statistical analysis and probabilistic reasoning over the inferences that can be made from mathematical models. This handbook presents a comprehensive guide to the discipline for practitioners and educators, in providing a full and detailed treatment of these important and emerging subjects. Leading experts in systems biology and statistics have come together to provide insight in to the major ideas in the field, and in particular methods of specifying and fitting models, and estimating the unknown parameters. This book: Provides a comprehensive account of inference techniques in systems biology. Introduces classical and Bayesian statistical methods for complex systems. Explores networks and graphical modeling as well as a wide range of statistical models for dynamical systems. Discusses various applications for statistical systems biology, such as gene regulation and signal transduction. Features statistical data analysis on numerous technologies, including metabolic and transcriptomic technologies. Presents an in-depth presentation of reverse engineering approaches. Provides colour illustrations to explain key concepts. This handbook will be a key resource for researchers practising systems biology, and those requiring a comprehensive overview of this important field.

Optimization Models and Computational Methods for Systems Biology

Author : Yang Cong
Publisher :
ISBN 13 : 9781361290033
Total Pages : pages
Book Rating : 4.2/5 (9 download)

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Book Synopsis Optimization Models and Computational Methods for Systems Biology by : Yang Cong

Download or read book Optimization Models and Computational Methods for Systems Biology written by Yang Cong and published by . This book was released on 2017-01-26 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "Optimization Models and Computational Methods for Systems Biology" by Yang, Cong, 丛阳, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Systems biology is a comprehensive quantitative analysis of the manner in which all the components of a biological system interact functionally along with time. Mathematical modeling and computational methods are indispensable in such kind of studies, especially for interpreting and predicting the complex interactions among all the components so as to obtain some desirable system properties. System dynamics, system robustness and control method are three crucial properties in systems biology. In this thesis, the above properties are studied in four different biological systems. The outbreak and spread of infectious diseases have been questioned and studied for years. The spread mechanism and prediction about the disease could enable scientists to evaluate isolation plans to have significant effects on a particular epidemic. A differential equation model is proposed to study the dynamics of HIV spread in a network of prisons. In prisons, screening and quarantining are both efficient control manners. An optimization model is proposed to study optimal strategies for the control of HIV spread in a prison system. A primordium (plural: primordia) is an organ or tissue in its earliest recognizable stage of development. Primordial development in plants is critical to the proper positioning and development of plant organs. An optimization model and two control mechanisms are proposed to study the dynamics and robustness of primordial systems. Probabilistic Boolean Networks (PBNs) are mathematical models for studying the switching behavior in genetic regulatory networks. An algorithm is proposed to identify singleton and small attractors in PBNs which correspond to cell types and cell states. The captured problem is NP-hard in general. Our algorithm is theoretically and computationally demonstrated to be much more efficient than the naive algorithm that examines all the possible states. The goal of studying the long-term behavior of a genetic regulatory network is to study the control strategies such that the system can obtain desired properties. A control method is proposed to study multiple external interventions meanwhile minimizing the control cost. Robustness is a paramount property for living organisms. The impact degree is a measure of robustness of a metabolic system against the deletion of single or multiple reaction(s). An algorithm is proposed to study the impact degree in Escherichia coli metabolic system. Moreover, approximation method based on Branching process is proposed for estimating the impact degree of metabolic networks. The effectiveness of our method is assured by testing with real-world Escherichia coli, Bacillus subtilis, Saccharomyces cerevisiae and Homo Sapiens metabolic systems. DOI: 10.5353/th_b4775284 Subjects: Systems biology - Mathematical models

Computational Methods in Systems Biology

Author : Ion Petre
Publisher : Springer Nature
ISBN 13 : 3031150341
Total Pages : 324 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Computational Methods in Systems Biology by : Ion Petre

Download or read book Computational Methods in Systems Biology written by Ion Petre and published by Springer Nature. This book was released on 2022-08-18 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.