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Recent Trends in Computational Omics: Concepts and Methodology, Pramod Katara


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Автор: Pramod Katara
Название:  Recent Trends in Computational Omics: Concepts and Methodology
ISBN: 9781536179415
Издательство: Nova Science
Классификация:

ISBN-10: 1536179418
Обложка/Формат: Hardback
Страницы: 478
Вес: 0.77 кг.
Дата издания: 22.07.2020
Язык: English
Размер: 140 x 210 x 23
Читательская аудитория: Professional & vocational
Ключевые слова: Computer programming / software development
Подзаголовок: Concepts and methodology
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Поставляется из: Англии
Описание: The last decade has witnessed various technological advances in life sciences, especially high throughput technologies. These technologies provide a way to perform parallel scientific studies in a very short period of time with low cost. High throughput techniques, mainly, next generation sequencing, microarray and mass spectrometry, have strengthened the omics vision in the last decades (study of complete system) and now resulted in well-developed branches of omics i.e., genomics, transcriptomics, proteomics and metabolomics, which deal with almost every level of central dogma of life. Practice of high throughput techniques throughout the world with different aims and objectives resulted in a voluminous data, which required computational applications, i.e., database, algorithm and software to store, process and get biological interpretation from primary raw data. Researchers from different fields are looking to analyze these raw data for different purposes, but lacking of proper information and knowledge in proper documented form creates different kinds of hurdles and raises the challenges. This book contains thirteen chapters that deal with different computational biology/bioinformatics resources and concepts which are already in practice by the scientific community or can be utilized to handle various aspects of different classes of omics data. It includes different computational concepts, algorithm, resources and recent trends belonging to the four major branches of omics (i.e., genomics, transcriptomics, proteomics and metabolomics), including integrative omics. It will help all scholars who are working in any branch of computational omics and bioinformatics field as well as those who would like to perform research at a systemic biology through computational approaches.

Artificial Intelligence for Finance Executives: The AI revolution, from industry trends and case studies to algorithms and concepts

Автор: Besse Alexis
Название: Artificial Intelligence for Finance Executives: The AI revolution, from industry trends and case studies to algorithms and concepts
ISBN: 1838356010 ISBN-13(EAN): 9781838356019
Издательство: Неизвестно
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Цена: 45980.00 T
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We often hear that AI is revolutionising the financial sector, like no other technology has done before. This book looks beyond these clich s and explores all aspects of this transformation at a deep level. It spells out a vision for the future and answers many questions that are routinely ignored.


What do we mean by Artificial Intelligence in finance? How do we move past the myths and misconceptions to reveal the key driving forces?

What are the industry trends that align with this transformation? Is it the explosion of digital touchpoints in retail, the reduced risk taking by investment banks, or the ascent of passive funds in asset management?

How do we develop concrete use cases from idea generation to production? How do we engineer systems to make accurate predictions, offer recommendations to clients, or analyse unstructured news data?

How do we build a successful data-driven organisation? What are the key pitfalls to avoid? Is it about culture, data governance, or management vision?

What are the risks specific to developing AI technologies? Can we humans understand and explain what the machines produce for us? Can we trust their predictions or actions?

What is the role of alternative data in all this? How can we put it to use for augmented insight?

What are the problems that AI is well equipped to solve? Is it all about neural networks and deep learning, as we regularly hear in the popular press? How do we understand human language, a task so important to the financial analyst?



The book is packed with concrete examples from the various disciplines of finance. Interested readers will also develop a deep understanding of AI algorithms - presented in plain English - and learn how to solve the most challenging problems. But first and foremost, it is a practical book that equips finance executives with everything they need to understand this transformation and to become agents of change themselves.



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