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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.
ICT Innovations 2020. Machine Learning and Applications
This book constitutes the refereed proceedings of the 12th International ICT Innovations Conference, ICT Innovations 2020, held in Skopje, North Macedonia, in September 2020. The 12 full papers and 6 short papers presented were carefully reviewed and selected from 60 submissions. The focal point of the volume is machine learning and applications in spheres of business, science and technology.
Abiotic Stress Signaling in Plants: Functional Genomic Intervention
Abiotic stresses such as high temperature, low-temperature, drought and salinity limit crop productivity worldwide. Understanding plant responses to these stresses is essential for rational engineering of crop plants. In Arabidopsis, the signal transduction pathways for abiotic stresses, light, several phytohormones and pathogenesis have been elucidated. A significant portion of plant genomes (Arabidopsis and rice were mostly studied) encodes for proteins involves in signaling such as receptor, sensors, kinases, phosphatases, transcription factors and transporters/channels. Despite decades of physiological and molecular effort, knowledge pertaining to how plants sense and transduce low and h...
Mathematical Approaches to Polymer Sequence Analysis and Related Problems
An edited volume describing the latest developments in approaching the problem of polymer sequence analysis, with special emphasis on the most relevant biopolymers (peptides and DNA) but not limited to them. The chapters will include peptide sequence analysis, DNA sequence analysis, analysis of biopolymers and nonpolymers, sequence alignment problems, and more.
Machine Learning and Knowledge Discovery in Databases
This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.
Data Management in Large-Scale Education Research
Research data management is becoming more complicated. Researchers are collecting more data, using more complex technologies, all the while increasing the visibility of our work with the push for data sharing and open science practices. Ad hoc data management practices may have worked for us in the past, but now others need to understand our processes as well, requiring researchers to be more thoughtful in planning their data management routines. This book is for anyone involved in a research study involving original data collection. While the book focuses on quantitative data, typically collected from human participants, many of the practices covered can apply to other types of data as well...
Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare
"This book provides methodologies and developments of grid technologies applied in different fields of life sciences"--Provided by publisher.
ICT Innovations 2018. Engineering and Life Sciences
This book constitutes the refereed proceedings of the 10th International ICT Innovations Conference, ICT Innovations 2018, held in Ohrid, Macedonia, in September 2018. The 21 full papers presented were carefully reviewed and selected from 81 submissions. They cover the following topics:sensor applications and deployments, embedded and cyber-physical systems, robotics, network architectures, cloud computing, software infrastructure, software creation and management, models of computation, computational complexity and cryptography, design and analysis of algorithms, mathematical optimization, probability and statistics, data management systems, data mining, human computer interaction (HCI), artificial intelligence, machine learning, life and medical sciences, health care information systems, bioinformatics.
