Artificial Intelligence for Molecular Biology: Advanced Methods and Applications
暫譯: 分子生物學的人工智慧：進階方法與應用

Nabeel Asim, Muhammad, Ahmed, Sheraz, Dengel, Andreas

Artificial Intelligence for Molecular Biology: Advanced Methods and Applications
  • 出版商: Springer
  • 出版日期: 2025-10-01
  • 售價: $3,490
  • 貴賓價: 9.5 折 $3,316
  • 語言: 英文
  • 頁數: 609
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3031904532
  • ISBN-13: 9783031904530
  • 相關分類: Large language model

    • 海外代購書籍(需單獨結帳)

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商品描述

The integration of artificial intelligence (AI) into molecular biology has brought about a paradigm shift, enabling researchers to tackle some of the most challenging problems in life sciences. This second volume builds upon the foundational principles explored in Volume I, delving into advanced AI methodologies and their applications in understanding biological sequences at a granular level. From word embeddings to language models, this volume examines the state-of-the-art techniques driving progress in molecular biology.

The chapters in this volume are structured to provide an in-depth exploration of AI methods and their transformative impact on DNA, RNA, protein, and peptide analysis:

    Word Embedding Methods: This chapter explores the evolution of word embedding techniques, including foundational models like Word2Vec, FastText, and GloVe, as well as advanced graph-based embeddings such as DeepWalk, Node2Vec, and Struc2Vec. These embeddings have revolutionized sequence representation, providing powerful tools for analyzing biological data. Large Language Models: Language models have reshaped the landscape of computational biology. This chapter examines models like ULMFiT, BERT, and cutting-edge tools like AlphaFold and RNAFormer, which have set new benchmarks in structure prediction and sequence analysis. AI-Driven Insights into DNA Sequence Analysis Landscape: AI has unlocked new possibilities in DNA analysis. This chapter reviews methodologies, datasets, and predictive pipelines, offering insights into the performance and distribution of research across various benchmarks. AI-Driven Insights into RNA Sequence Analysis Landscape: RNA, with its unique roles and complexities, benefits significantly from AI approaches. This chapter investigates datasets, predictive pipelines, and performance metrics specific to RNA analysis. AI-Driven Insights into Protein Sequence Analysis Landscape: Proteins, central to numerous biological processes, are analyzed using AI-driven techniques. This chapter discusses embedding-based and language model-based methods, as well as the resources and benchmarks available for protein analysis. AI-Driven Revolution in Peptide Classification Landscape: Peptides, due to their diverse biological roles, pose unique challenges. This chapter provides a thorough examination of peptide classification, exploring AI methodologies, datasets, evaluation strategies, and the state-of-the-art performance of predictive models.
Volume II provides a detailed narrative of how advanced AI methodologies are transforming the study of molecular biology. Each chapter bridges the gap between theoretical advancements and practical applications, equipping researchers and practitioners with the knowledge needed to drive innovation in this interdisciplinary field.

商品描述(中文翻譯)

人工智慧（AI）與分子生物學的整合帶來了範式轉變，使研究人員能夠解決生命科學中一些最具挑戰性的問題。本卷基於第一卷中探討的基礎原則，深入研究先進的AI方法及其在理解生物序列方面的應用，從字嵌入到語言模型，本卷檢視了推動分子生物學進展的最先進技術。

本卷的章節結構旨在深入探討AI方法及其對DNA、RNA、蛋白質和肽分析的變革性影響：

1. **字嵌入方法**：本章探討字嵌入技術的演變，包括Word2Vec、FastText和GloVe等基礎模型，以及DeepWalk、Node2Vec和Struc2Vec等先進的基於圖的嵌入技術。這些嵌入技術徹底改變了序列表示，為分析生物數據提供了強大的工具。

2. **大型語言模型**：語言模型重塑了計算生物學的格局。本章檢視了ULMFiT、BERT等模型，以及像AlphaFold和RNAFormer這樣的尖端工具，這些工具在結構預測和序列分析中設立了新的基準。

3. **AI驅動的DNA序列分析洞察**：AI為DNA分析開啟了新的可能性。本章回顧了方法論、數據集和預測管道，提供了對各種基準下研究表現和分佈的洞察。

4. **AI驅動的RNA序列分析洞察**：RNA因其獨特的角色和複雜性，從AI方法中獲益良多。本章調查了特定於RNA分析的數據集、預測管道和性能指標。

5. **AI驅動的蛋白質序列分析洞察**：蛋白質在眾多生物過程中扮演核心角色，使用AI驅動的技術進行分析。本章討論了基於嵌入和語言模型的方法，以及可用於蛋白質分析的資源和基準。

6. **AI驅動的肽分類革命**：肽因其多樣的生物角色而面臨獨特挑戰。本章對肽分類進行了徹底的檢視，探討了AI方法論、數據集、評估策略以及預測模型的最先進性能。

第二卷詳細敘述了先進的AI方法如何改變分子生物學的研究。每一章都在理論進展與實際應用之間架起橋樑，為研究人員和實踐者提供了推動這一跨學科領域創新的所需知識。

作者簡介

Muhammad Nabeel Asim is a Senior Researcher at the German Research Center for Artificial Intelligence (DFKI) and a co-founder of intelligentX. He earned his Ph.D. with summa cum laude distinction from Technische Universität Kaiserslautern, Germany, where his research focused on developing an AI-driven framework capable of generating innovative predictive pipelines for genomics, proteomics, and multi-omics data analysis. Nabeel has an extensive publication record in areas such as DNA, RNA, and protein sequence analysis. Beyond genomics, he has applied his expertise in artificial intelligence to create diverse real-world solutions across various domains, including natural language processing, energy, and network security. Currently, he is committed to mentoring future researchers and developing innovative AI solutions to address critical global challenges.

Sheraz Ahmed is a Principal Researcher at the German Research Center for Artificial Intelligence (DFKI) while running DeepReader GmbH, a company he founded to bridge the gap between academic research and industry applications. He earned his Ph.D. from Technische Universität Kaiserslautern, Germany, focusing on innovative approaches to breaking down and understanding information in document images. His work has increasingly turned toward the Life Sciences, where he sees AI as a powerful tool for accelerating scientific breakthroughs. He is also dedicated to advancing trustworthy AI, ensuring that AI technologies are ethical, transparent, and reliable for widespread adoption. In recognition of his outstanding ocontributions, Sheraz was honored with the prestigious DFKI Research Fellow Award, highlighting his leadership in the field of artificial intelligence. Multiple research stays backed by prestigious JSPS and DAAD fellowships, have shaped his international outlook on AI development. Today, he continues to explore new frontiers in AI while mentoring the next generation of researchers and building practical solutions for real-world challenges.

Andreas Dengel is a professor at the Department of Computer Science at the University of Kaiserslautern-Landau, a co-founder of intelligentX as well as the Executive Director of DFKI in Kaiserslautern. Since 2009, he has held another professorship (kyakuin) at the Department of Computer Science and Intelligent Systems at Osaka Metropolitan University, with the right to teach and examine. At this university, he was also appointed "Distinguished Honorary Professor" (tokubetu eiyo kyoju) in March 2018, an honor bestowed on only five researchers in 135 years. He has received many honors for his work and scientific achievements. In 2019 he was selected by a jury on behalf of the German Federal Ministry of Education and Research (BMBF) as one of the most influential scientists in 50 years of AI history in Germany for his research in the field of document analysis. He is the recipient of the Order of Merit of Rhineland-Palatinate and was awarded the "The Order of the Rising Sun, Gold Rays with Neck Ribbon" in 2021, Japan's oldest order, on behalf of His Majesty Emperor Naruhito. Andreas Dengel has chaired numerous international conferences and is a member of the editorial boards of international journals and book series. He has written or edited 14 books and is the author of more than 600 peer-reviewed scientific publications, many of which have received the Best Paper Award. His main research areas are machine learning, pattern recognition, quantified learning, data mining, and neuro-symbolic AI.

作者簡介(中文翻譯)

穆罕默德·納比爾·阿西姆（Muhammad Nabeel Asim）是德國人工智慧研究中心（DFKI）的高級研究員，也是intelligentX的共同創辦人。他在德國凱瑟斯勞滕工業大學（Technische Universität Kaiserslautern）獲得了以優異成績（summa cum laude）取得的博士學位，研究重點是開發一個能夠生成創新預測管道的人工智慧驅動框架，應用於基因組學、蛋白質組學和多組學數據分析。納比爾在DNA、RNA和蛋白質序列分析等領域擁有豐富的出版記錄。除了基因組學，他還將其在人工智慧方面的專業知識應用於創造多樣的現實世界解決方案，涵蓋自然語言處理、能源和網絡安全等多個領域。目前，他致力於指導未來的研究人員，並開發創新的人工智慧解決方案，以應對全球面臨的重大挑戰。

謝拉茲·艾哈邁德（Sheraz Ahmed）是德國人工智慧研究中心（DFKI）的首席研究員，同時經營他創辦的DeepReader GmbH，該公司旨在縮短學術研究與產業應用之間的距離。他在德國凱瑟斯勞滕工業大學獲得博士學位，專注於創新方法以解析和理解文件圖像中的信息。他的工作越來越多地轉向生命科學領域，並認為人工智慧是加速科學突破的強大工具。他還致力於推進可信的人工智慧，確保人工智慧技術在廣泛應用中是道德的、透明的和可靠的。因其卓越的貢獻，謝拉茲獲得了享有盛譽的DFKI研究獎學金，突顯了他在人工智慧領域的領導地位。多次獲得JSPS和DAAD獎學金的研究經歷，塑造了他對人工智慧發展的國際視野。如今，他繼續探索人工智慧的新前沿，同時指導下一代研究人員，並為現實世界的挑戰構建實用解決方案。

安德烈亞斯·登格爾（Andreas Dengel）是凱瑟斯勞滕-蘭道大學計算機科學系的教授，也是intelligentX的共同創辦人，以及DFKI凱瑟斯勞滕的執行董事。自2009年以來，他在大阪市立大學的計算機科學與智能系擔任另一個教授職位（客員教授），擁有教學和考試的權利。在該大學，他於2018年3月被任命為「傑出名譽教授」（特別榮譽教授），這一榮譽在135年來僅授予五位研究人員。他因其工作和科學成就獲得了許多榮譽。2019年，他被德國聯邦教育與研究部（BMBF）選為50年人工智慧歷史中最具影響力的科學家之一，因其在文件分析領域的研究。他是萊茵-普法爾茨州功勳勳章的獲得者，並於2021年獲得日本最古老的勳章「旭日章金光帶」，由德仁天皇代表頒發。安德烈亞斯·登格爾主持過多次國際會議，並擔任國際期刊和書籍系列的編輯委員會成員。他撰寫或編輯了14本書籍，並發表了超過600篇經過同行評審的科學出版物，其中許多獲得了最佳論文獎。他的主要研究領域包括機器學習、模式識別、量化學習、數據挖掘和神經符號人工智慧。

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