Computational Life Sciences Ii PDF Download
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| Author | : Michael R. Berthold |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 279 |
| Release | : 2006-09-21 |
| Genre | : Computers |
| ISBN | : 3540457674 |
Download Computational Life Sciences II Book in PDF, ePub and Kindle
This book constitutes the refereed proceedings of the Second International Symposium on Computational Life Sciences, CompLife 2006, held in Cambridge, UK, in September 2006.The 25 revised full papers presented were carefully reviewed and selected from 56 initial submissions. The papers are organized in topical sections on genomics, data mining, molecular simulation, molecular informatics, systems biology, biological networks/metabolism, and computational neuroscience.
| Author | : Cannataro, Mario |
| Publisher | : IGI Global |
| Total Pages | : 960 |
| Release | : 2009-05-31 |
| Genre | : Medical |
| ISBN | : 1605663751 |
Download Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare Book in PDF, ePub and Kindle
"This book provides methodologies and developments of grid technologies applied in different fields of life sciences"--Provided by publisher.
| Author | : Jens Dörpinghaus |
| Publisher | : Springer Nature |
| Total Pages | : 593 |
| Release | : 2023-03-04 |
| Genre | : Computers |
| ISBN | : 303108411X |
Download Computational Life Sciences Book in PDF, ePub and Kindle
This book broadly covers the given spectrum of disciplines in Computational Life Sciences, transforming it into a strong helping hand for teachers, students, practitioners and researchers. In Life Sciences, problem-solving and data analysis often depend on biological expertise combined with technical skills in order to generate, manage and efficiently analyse big data. These technical skills can easily be enhanced by good theoretical foundations, developed from well-chosen practical examples and inspiring new strategies. This is the innovative approach of Computational Life Sciences-Data Engineering and Data Mining for Life Sciences: We present basic concepts, advanced topics and emerging technologies, introduce algorithm design and programming principles, address data mining and knowledge discovery as well as applications arising from real projects. Chapters are largely independent and often flanked by illustrative examples and practical advise.
| Author | : Kholmirzo Kholmurodov |
| Publisher | : Nova Science Publishers |
| Total Pages | : 0 |
| Release | : 2015 |
| Genre | : Molecular biology |
| ISBN | : 9781634825412 |
Download Computational Materials and Biological Sciences Book in PDF, ePub and Kindle
In this book, original papers have been collected to demonstrate the efficient use of computer molecular dynamics simulation methods for the studying of nanoscale phenomena in the materials and life sciences. This book discusses modern molecular simulation methods for the study of molecular shape and properties in protein and polymer engineering, drugs and materials design, structure-function relationships, and related issues. This book contains the Proceedings of the MSSMBS-2014 and DSCMBS-2014 International Workshops which have been organised by the Joint Institute for Nuclear Research, the Institute of Bioorganic Chemistry of the Russian Academy of Sciences and S.U. Umarov Physical-Technical Institute of the Academy of Sciences of the Republic of Tajikistan. The research topics discussed in the MSSMBS'14 & DSCMBS'14 International Workshops are as follows: computer molecular simulation methods and approaches; molecular dynamics and Monte-Carlo techniques; modelling of biological molecules; physical and biochemical systems; material fabrication and design; drug design in medicine; computational and computing physics, chemistry, biology and medicine; GPU accelerated molecular dynamics and related techniques.
| Author | : Noor Ahmad Shaik |
| Publisher | : Springer Nature |
| Total Pages | : 309 |
| Release | : 2019-10-18 |
| Genre | : Science |
| ISBN | : 3030183750 |
Download Essentials of Bioinformatics, Volume II Book in PDF, ePub and Kindle
Bioinformatics is an integrative field of computer science, genetics, genomics, proteomics, and statistics, which has undoubtedly revolutionized the study of biology and medicine in past decades. It mainly assists in modeling, predicting and interpreting large multidimensional biological data by utilizing advanced computational methods. Despite its enormous potential, bioinformatics is not widely integrated into the academic curriculum as most life science students and researchers are still not equipped with the necessary knowledge to take advantage of this powerful tool. Hence, the primary purpose of our book is to supplement this unmet need by providing an easily accessible platform for students and researchers starting their career in life sciences. This book aims to avoid sophisticated computational algorithms and programming. Instead, it focuses on simple DIY analysis and interpretation of biological data with personal computers. Our belief is that once the beginners acquire these basic skillsets, they will be able to handle most of the bioinformatics tools for their research work and to better understand their experimental outcomes. Our second title of this volume set In Silico Life Sciences: Medicine provides hands-on experience in analyzing high throughput molecular data for the diagnosis, prognosis, and treatment of monogenic or polygenic human diseases. The key concepts in this volume include risk factor assessment, genetic tests and result interpretation, personalized medicine, and drug discovery. This volume is expected to train readers in both single and multi-dimensional biological analysis using open data sets, and provides a unique learning experience through clinical scenarios and case studies.
| Author | : Emmanuel Barillot |
| Publisher | : CRC Press |
| Total Pages | : 463 |
| Release | : 2012-08-25 |
| Genre | : Science |
| ISBN | : 1439831440 |
Download Computational Systems Biology of Cancer Book in PDF, ePub and Kindle
The future of cancer research and the development of new therapeutic strategies rely on our ability to convert biological and clinical questions into mathematical models—integrating our knowledge of tumour progression mechanisms with the tsunami of information brought by high-throughput technologies such as microarrays and next-generation sequencing. Offering promising insights on how to defeat cancer, the emerging field of systems biology captures the complexity of biological phenomena using mathematical and computational tools. Novel Approaches to Fighting Cancer Drawn from the authors’ decade-long work in the cancer computational systems biology laboratory at Institut Curie (Paris, France), Computational Systems Biology of Cancer explains how to apply computational systems biology approaches to cancer research. The authors provide proven techniques and tools for cancer bioinformatics and systems biology research. Effectively Use Algorithmic Methods and Bioinformatics Tools in Real Biological Applications Suitable for readers in both the computational and life sciences, this self-contained guide assumes very limited background in biology, mathematics, and computer science. It explores how computational systems biology can help fight cancer in three essential aspects: Categorising tumours Finding new targets Designing improved and tailored therapeutic strategies Each chapter introduces a problem, presents applicable concepts and state-of-the-art methods, describes existing tools, illustrates applications using real cases, lists publically available data and software, and includes references to further reading. Some chapters also contain exercises. Figures from the text and scripts/data for reproducing a breast cancer data analysis are available at www.cancer-systems-biology.net.
| Author | : Benny Chor |
| Publisher | : Cambridge University Press |
| Total Pages | : 0 |
| Release | : 2022-08-31 |
| Genre | : Computers |
| ISBN | : 9781316647592 |
Download Computational Thinking for Life Scientists Book in PDF, ePub and Kindle
Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy required for any modern biologist to adopt computational approaches in their research with confidence.
| Author | : Lars Linsen |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 285 |
| Release | : 2012-01-11 |
| Genre | : Mathematics |
| ISBN | : 3642216080 |
Download Visualization in Medicine and Life Sciences II Book in PDF, ePub and Kindle
For some time, medicine has been an important driver for the development of data processing and visualization techniques. Improved technology offers the capacity to generate larger and more complex data sets related to imaging and simulation. This, in turn, creates the need for more effective visualization tools for medical practitioners to interpret and utilize data in meaningful ways. The first edition of Visualization in Medicine and Life Sciences (VMLS) emerged from a workshop convened to explore the significant data visualization challenges created by emerging technologies in the life sciences. The workshop and the book addressed questions of whether medical data visualization approaches can be devised or improved to meet these challenges, with the promise of ultimately being adopted by medical experts. Visualization in Medicine and Life Sciences II follows the second international VMLS workshop, held in Bremerhaven, Germany, in July 2009. Internationally renowned experts from the visualization and driving application areas came together for this second workshop. The book presents peer-reviewed research and survey papers which document and discuss the progress made, explore new approaches to data visualization, and assess new challenges and research directions.
| Author | : Saleh Alkhalifa |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 408 |
| Release | : 2022-01-28 |
| Genre | : Mathematics |
| ISBN | : 1801815674 |
Download Machine Learning in Biotechnology and Life Sciences Book in PDF, ePub and Kindle
Explore all the tools and templates needed for data scientists to drive success in their biotechnology careers with this comprehensive guide Key FeaturesLearn the applications of machine learning in biotechnology and life science sectorsDiscover exciting real-world applications of deep learning and natural language processingUnderstand the general process of deploying models to cloud platforms such as AWS and GCPBook Description The booming fields of biotechnology and life sciences have seen drastic changes over the last few years. With competition growing in every corner, companies around the globe are looking to data-driven methods such as machine learning to optimize processes and reduce costs. This book helps lab scientists, engineers, and managers to develop a data scientist's mindset by taking a hands-on approach to learning about the applications of machine learning to increase productivity and efficiency in no time. You'll start with a crash course in Python, SQL, and data science to develop and tune sophisticated models from scratch to automate processes and make predictions in the biotechnology and life sciences domain. As you advance, the book covers a number of advanced techniques in machine learning, deep learning, and natural language processing using real-world data. By the end of this machine learning book, you'll be able to build and deploy your own machine learning models to automate processes and make predictions using AWS and GCP. What you will learnGet started with Python programming and Structured Query Language (SQL)Develop a machine learning predictive model from scratch using PythonFine-tune deep learning models to optimize their performance for various tasksFind out how to deploy, evaluate, and monitor a model in the cloudUnderstand how to apply advanced techniques to real-world dataDiscover how to use key deep learning methods such as LSTMs and transformersWho this book is for This book is for data scientists and scientific professionals looking to transcend to the biotechnology domain. Scientific professionals who are already established within the pharmaceutical and biotechnology sectors will find this book useful. A basic understanding of Python programming and beginner-level background in data science conjunction is needed to get the most out of this book.
| Author | : Michael R. Berthold |
| Publisher | : Springer |
| Total Pages | : 280 |
| Release | : 2005-09-16 |
| Genre | : Science |
| ISBN | : 9783540291046 |
Download Computational Life Sciences Book in PDF, ePub and Kindle
This book constitutes the refereed proceedings of the First International Symposium on Computational Life Sciences, CompLife 2005, held in Konstanz, Germany in September 2005. The 21 revised full papers presented together with 3 papers of a workshop on Distributed Data Mining in the Life Sciences (LifeDDM) were carefully reviewed and selected from 49 initial submissions. The papers cover areas ranging from high-level system biology to data analysis related to mass spec traces and are organized in topical sections on systems biology, data analysis and integration, structural biology, genomics, computational proteomics, molecular informatics, molecular structure determination and simulation, and distributed data mining.
