Automated Reasoning for Systems Biology and Medicine
Mentés helye:
| Testületi szerző: | |
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| Közreműködő(k): | |
| Különgyűjtemény: | e-book |
| Formátum: | könyv |
| Nyelv: | angol |
| Megjelenés: |
Cham : Springer International Publishing,
2019
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| Sorozat: | Computational Biology, ISSN 1568-2684 ; 30 |
| Tárgyszavak: | |
| Online elérés: | http://doi.org/10.1007/978-3-030-17297-8 |
| Címkék: |
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A tételhez itt fűzhet saját címkét!
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| id |
opac-EUL01-001013155 |
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| collection |
e-book |
| institution |
L_042 EUL01 |
| spelling |
Automated Reasoning for Systems Biology and Medicine edited by Pietro Liò, Paolo Zuliani Cham Springer International Publishing 2019 XI, 474 p. 214 illusztrált, 77 illusztrált szinesben online forrás szöveg txt rdacontent számítógépes c rdamedia távoli hozzáférés cr rdacarrier szövegfájl PDF rda Computational Biology 1568-2684 30 Part I: Model Checking -- Chapter 1. Model Checking Approach to the Analysis of Biological Systems -- Chapter2. Automated Reasoning for the Synthesis and Analysis of Biological Programs -- Chapter 3. Statistical Model Checking based Analysis Techniques of Biological Networks -- Chapter 4. Models, Devices, Properties and Verification for the Artificial Pancreas -- Chapter 5. Using State Space Exploration to Determine How Gene Regulatory Networks Constrain Mutation Order in Cancer Evolution -- Part II: Formal Methods and Logic -- Chapter 6. Set-based Analysis for Biological Modelling -- Chapter 7. Logic and Linear Programs to Understand Cancer Response -- Chapter 8. Logic-Based Formalization of System Requirements for Integrated Clinical Environments -- Chapter 9. Balancing prescriptions with Constraint Solvers -- Chapter 10. Metastable Regimes and Tipping Points of Biochemical Networks with Potential Applications in Precision Medicine -- Part III: Stochastic Modelling and Analysis.-Chapter 11. Stochastic Spatial Modelling of the Remyelination Process in Multiple Sclerosis Lesions -- Chapter 12. Approximation Techniques for Stochastic Analysis of Biological Systems -- Chapter 13. A Graphical Approach for the Hybrid Modelling of Intracellular Calcium Dynamics Based on Coloured Hybrid Petri Nets -- Chapter 14. Methods for Personalised Delivery Rate Computation for IV Administered Anesthetic Propofol -- Part IV: Machine Learning and Artificial Intelligence -- Chapter 15. Towards the Integration of Metabolic Network Modelling and Machine Learning for the Routine Analysis of High-Throughput Patient Data -- Chapter 16. Opportunities and Challenges in Applying Artificial Intelligence to Bioengineering -- Chapter 17. Deep Learning with Convolutional Neural Networks for Histopathology Image Analysis. This book presents outstanding contributions in an exciting, new and multidisciplinary research area: the application of formal, automated reasoning techniques to analyse complex models in systems biology and systems medicine. Automated reasoning is a field of computer science devoted to the development of algorithms that yield trustworthy answers, providing a basis of sound logical reasoning. For example, in the semiconductor industry formal verification is instrumental to ensuring that chip designs are free of defects (or “bugs”). Over the past 15 years, systems biology and systems medicine have been introduced in an attempt to understand the enormous complexity of life from a computational point of view. This has generated a wealth of new knowledge in the form of computational models, whose staggering complexity makes manual analysis methods infeasible. Sound, trusted, and automated means of analysing the models are thus required in order to be able to trust their conclusions. Above all, this is crucial to engineering safe biomedical devices and to reducing our reliance on wet-lab experiments and clinical trials, which will in turn produce lower economic and societal costs. Some examples of the questions addressed here include: Can we automatically adjust medications for patients with multiple chronic conditions? Can we verify that an artificial pancreas system delivers insulin in a way that ensures Type 1 diabetic patients never suffer from hyperglycaemia or hypoglycaemia? And lastly, can we predict what kind of mutations a cancer cell is likely to undergo? This book brings together leading researchers from a number of highly interdisciplinary areas, including: · Parameter inference from time series · Model selection · Network structure identification · Machine learning · Systems medicine · Hypothesis generation from experimental data · Systems biology, systems medicine, and digital pathology · Verification of biomedical devices “This b Nyomtatott kiadás: ISBN 9783030172961 Nyomtatott kiadás: ISBN 9783030172985 Nyomtatott kiadás: ISBN 9783030172992 Az e-könyvek a teljes ELTE IP-tartományon belül online elérhetők. e-book könyv bioinformatika rendszerbiológia alakfelismerés egészségügyi informatika gépi tanulás mesterséges intelligencia informatika Bioinformatics. Systems biology Artificial intelligence. Health informatics. Pattern recognition. elektronikus könyv Liò, Pietro szerk. Zuliani, Paolo szerk. SpringerLink (Online service) közreadó testület Computational Biology Online változat http://doi.org/10.1007/978-3-030-17297-8 Cham Springer International Publishing Imprint: Springer 2019 EUL01 |
| language |
English |
| format |
Book |
| author2 |
Liò, Pietro, szerk. Zuliani, Paolo, szerk. |
| author_facet |
Liò, Pietro, szerk. Zuliani, Paolo, szerk. SpringerLink (Online service), közreadó testület |
| author_corporate |
SpringerLink (Online service), közreadó testület |
| author_sort |
Liò, Pietro |
| title |
Automated Reasoning for Systems Biology and Medicine |
| spellingShingle |
Automated Reasoning for Systems Biology and Medicine Computational Biology, ISSN 1568-2684 ; 30 bioinformatika rendszerbiológia alakfelismerés egészségügyi informatika gépi tanulás -- mesterséges intelligencia -- informatika Bioinformatics. Systems biology Artificial intelligence. Health informatics. Pattern recognition. elektronikus könyv |
| title_short |
Automated Reasoning for Systems Biology and Medicine |
| title_full |
Automated Reasoning for Systems Biology and Medicine edited by Pietro Liò, Paolo Zuliani |
| title_fullStr |
Automated Reasoning for Systems Biology and Medicine edited by Pietro Liò, Paolo Zuliani |
| title_full_unstemmed |
Automated Reasoning for Systems Biology and Medicine edited by Pietro Liò, Paolo Zuliani |
| title_auth |
Automated Reasoning for Systems Biology and Medicine |
| title_sort |
automated reasoning for systems biology and medicine |
| series |
Computational Biology, ISSN 1568-2684 ; 30 |
| series2 |
Computational Biology |
| publishDate |
2019 |
| publishDateSort |
2019 |
| physical |
XI, 474 p. 214 illusztrált, 77 illusztrált szinesben : online forrás |
| isbn |
978-3-030-17297-8 |
| issn |
1568-2684 |
| callnumber-first |
Q - Science |
| callnumber-subject |
QH - Natural History and Biology |
| callnumber-label |
QH324 |
| callnumber-raw |
15631 |
| callnumber-search |
15631 |
| topic |
bioinformatika rendszerbiológia alakfelismerés egészségügyi informatika gépi tanulás -- mesterséges intelligencia -- informatika Bioinformatics. Systems biology Artificial intelligence. Health informatics. Pattern recognition. elektronikus könyv |
| topic_facet |
bioinformatika rendszerbiológia alakfelismerés egészségügyi informatika gépi tanulás -- mesterséges intelligencia -- informatika Bioinformatics. Systems biology Artificial intelligence. Health informatics. Pattern recognition. elektronikus könyv bioinformatika rendszerbiológia alakfelismerés egészségügyi informatika gépi tanulás Bioinformatics. Systems biology Artificial intelligence. Health informatics. Pattern recognition. mesterséges intelligencia informatika |
| url |
http://doi.org/10.1007/978-3-030-17297-8 |
| illustrated |
Illustrated |
| dewey-hundreds |
500 - Science |
| dewey-tens |
570 - Life sciences; biology |
| dewey-ones |
570 - Life sciences; biology |
| dewey-full |
570.285 |
| dewey-sort |
3570.285 |
| dewey-raw |
570.285 |
| dewey-search |
570.285 |
| first_indexed |
2023-12-27T20:07:37Z |
| last_indexed |
2023-12-30T20:55:01Z |
| recordtype |
opac |
| publisher |
Cham : Springer International Publishing |
| _version_ |
1786737959139016704 |
| score |
13,366924 |
| generalnotes |
This book presents outstanding contributions in an exciting, new and multidisciplinary research area: the application of formal, automated reasoning techniques to analyse complex models in systems biology and systems medicine. Automated reasoning is a field of computer science devoted to the development of algorithms that yield trustworthy answers, providing a basis of sound logical reasoning. For example, in the semiconductor industry formal verification is instrumental to ensuring that chip designs are free of defects (or “bugs”). Over the past 15 years, systems biology and systems medicine have been introduced in an attempt to understand the enormous complexity of life from a computational point of view. This has generated a wealth of new knowledge in the form of computational models, whose staggering complexity makes manual analysis methods infeasible. Sound, trusted, and automated means of analysing the models are thus required in order to be able to trust their conclusions. Above all, this is crucial to engineering safe biomedical devices and to reducing our reliance on wet-lab experiments and clinical trials, which will in turn produce lower economic and societal costs. Some examples of the questions addressed here include: Can we automatically adjust medications for patients with multiple chronic conditions? Can we verify that an artificial pancreas system delivers insulin in a way that ensures Type 1 diabetic patients never suffer from hyperglycaemia or hypoglycaemia? And lastly, can we predict what kind of mutations a cancer cell is likely to undergo? This book brings together leading researchers from a number of highly interdisciplinary areas, including: · Parameter inference from time series · Model selection · Network structure identification · Machine learning · Systems medicine · Hypothesis generation from experimental data · Systems biology, systems medicine, and digital pathology · Verification of biomedical devices “This b |