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Serum
For Ronit Levy, leaving Israel appears to be the only way of escaping her ex-boyfriend’s unrelenting barrage of assaults. Reconciliation is totally out of the question. She desperately yearns for a lasting inner-peace, a peace without further threat of emotional anguish. However, her psychopathic ex-lover, John Rothman, is determined to exact his bloody revenge on the only woman who ever walked out on him. In his drugged state, he concocts a sadistic plan to bring closure to the matter. With her disabled brother entrusted into the care of a family friend, Ronit leaves for her new post in Tal Basta, Egypt. The Al-Radah-Corporation, a pharmaceutical monolith, is Ronit’s sanctuary; a place ...
Microbiome and Machine Learning, Volume II
Due to the success of Microbiome and Machine Learning, which collected research results and perspectives of researchers working in the field of machine learning (ML) applied to the analysis of microbiome data, we are launching the second volume to collate any new findings in the field to further our understanding and encourage the participation of experts worldwide in the discussion. The success of ML algorithms in the field is substantially due to their capacity to process high-dimensional data and deal with uncertainty and noise. However, to maximize the combinatory potential of these emerging fields (microbiome and ML), researchers have to deal with some aspects that are complex and inherently related to microbiome data. Microbiome data are convoluted, noisy and highly variable, and non-standard analytical methodologies are required to unlock their clinical and scientific potential. Therefore, although a wide range of statistical modelling and ML methods are available, their application is only sometimes optimal when dealing with microbiome data.
Applying Machine Learning Techniques to Bioinformatics: Few-Shot and Zero-Shot Methods
Why are cutting-edge data science techniques such as bioinformatics, few-shot learning, and zero-shot learning underutilized in the world of biological sciences?. In a rapidly advancing field, the failure to harness the full potential of these disciplines limits scientists ability to unlock critical insights into biological systems, personalized medicine, and biomarker identification. This untapped potential hinders progress and limits our capacity to tackle complex biological challenges. The solution to this issue lies within the pages of Applying Machine Learning Techniques to Bioinformatics. This book serves as a powerful resource, offering a comprehensive analysis of how these emerging disciplines can be effectively applied to the realm of biological research. By addressing these challenges and providing in-depth case studies and practical implementations, the book equips researchers, scientists, and curious minds with the knowledge and techniques needed to navigate the ever-changing landscape of bioinformatics and machine learning within the biological sciences.
Autophagy in tumor and tumor microenvironment
This book deals with the paradoxical role of autophagy in tumor suppression and tumor promotion in cancer cells. Autophagy plays opposing, context-dependent roles in tumors; accordingly, strategies based on inhibiting or stimulating autophagy could offer as potential cancer therapies. The book elucidates the physiological role of autophagy in modulating cancer metastasis, which is the primary cause of cancer-associated mortality. Further, it reviews its role in the differentiation, development, and activation of multiple immune cells, and its potential applications in tumor immunotherapy. In addition, it examines the effect of epigenetic modifications of autophagy-associated genes in regulating tumor growth and therapeutic response and summarizes autophagy’s role in the development of resistance to a variety of anti-cancer drugs in cancer cells. In closing, it assesses autophagy as a potential therapeutic target for cancer treatment. Given its scope, the book offers a valuable asset for all oncologists and researchers who wish to understand the potential role of autophagy in tumor biology.
Database and Expert Systems Applications
This volume constitutes the refereed proceedings of the three workshops held at the 31st International Conference on Database and Expert Systems Applications, DEXA 2020, held in September 2020: The 11th International Workshop on Biological Knowledge Discovery from Data, BIOKDD 2020, the 4th International Workshop on Cyber-Security and Functional Safety in Cyber-Physical Systems, IWCFS 2020, the 2nd International Workshop on Machine Learning and Knowledge Graphs, MLKgraphs2019. Due to the COVID-19 pandemic the conference and workshops were held virtually. The 10 papers were thoroughly reviewed and selected from 15 submissions, and discuss a range of topics including: knowledge discovery, biological data, cyber security, cyber-physical system, machine learning, knowledge graphs, information retriever, data base, and artificial intelligence.
PRICAI 2006: Trends in Artificial Intelligence
This book constitutes the refereed proceedings of the 9th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2006, held in Guilin, China in August 2006. The book presents 81 revised full papers and 87 revised short papers together with 3 keynote talks. The papers are organized in topical sections on intelligent agents, automated reasoning, machine learning and data mining, natural language processing and speech recognition, computer vision, perception and animation, and more.
Database and Expert Systems Applications
This volume constitutes the refereed proceedings of the three workshops held at the 29th International Conference on Database and Expert Systems Applications, DEXA 2018, held in Regensburg, Germany, in September 2018: the Third International Workshop on Big Data Management in Cloud Systems, BDMICS 2018, the 9th International Workshop on Biological Knowledge Discovery from Data, BIOKDD, and the 15th International Workshop on Technologies for Information Retrieval, TIR. The 25 revised full papers were carefully reviewed and selected from 33 submissions. The papers discuss a range of topics including: parallel data management systems, consistency and privacy cloud computing and graph queries, web and domain corpora, NLP applications, social media and personalization
Neural Information Processing
The three volume set LNCS 4232, LNCS 4233, and LNCS 4234 constitutes the refereed proceedings of the 13th International Conference on Neural Information Processing, ICONIP 2006, held in Hong Kong, China in October 2006. The 386 revised full papers presented were carefully reviewed and selected from 1175 submissions.
Database and Expert Systems Applications
This volume constitutes the refereed proceedings of the four workshops held at the 30th International Conference on Database and Expert Systems Applications, DEXA 2019, held in Linz, Austria, in August 2019: The 10th International Workshop on Biological Knowledge Discovery from Data, BIOKDD 2019, the 3rd International Workshop on Cyber-Security and Functional Safety in Cyber-Physical Systems, IWCFS 2019, the 1st International Workshop on Machine Learning and Knowledge Graphs, MLKgraphs2019, and the 16th International Workshop on Technologies for Information Retrieval, TIR 2019. The 26 selected papers discuss a range of topics including: knowledge discovery, biological data, cyber security, cyber-physical system, machine learning, knowledge graphs, information retriever, data base, and artificial intelligent.
