Motivation and Objectives.

Genomics is concerned with the sequencing and analysis of an organism’s genome. It is involved in the understanding of how every single gene can affect the entire genome. This goal is mainly afforded using the current, cost-effective, high throughput sequencing technologies. These technologies produce a huge amount of data that usually require high performance computing solutions and opens new ways for the study of genomics, but also transcriptomics, gene expression, and systems biology, among others. The continuous improvements and broader applications on sequencing technologies is producing a continuous new demand of improved high-throughput bioinformatics tools. Genomics is concerned with the sequencing and analysis of an organism genome taking advantage of the current, cost-effective, high throughput sequencing technologies. Continuous improvement on genomics is producing a continuous new demand of enhanced high-throughput bioinformatics tools. In this context, the generation, integration and interpretation of genetic and genomic data is driving a new era of healthcare and patient management. Medical genomics (or genomic medicine) is this emerging discipline that involves the use of genomic information about a patient as part of the clinical care with diagnostic or therapeutic purposes to improve the health outcomes. Moreover, it can be considered a subset of precision medicine that is having an impact in the fields of oncology, pharmacology, rare and undiagnosed diseases, and infectious diseases.The aim of this special session is to bring together researchers in medicine, genomics, and bioinformatics to translate medical genomics research into new diagnostic, therapeutic, and preventive medical approaches. Therefore, we invite authors to submit original research, new tools or pipelines, or their update, and review articles on relevant topics, such as (but not limited to):

• Tools for data pre-processing (quality control and filtering)
• Tools for sequence mapping
• Tools for the comparison of two read libraries without an external reference.
• Tools for genomic variants (such as variant calling or variant annotation)
• Tools for functional annotation: identification of domains, orthologues, genetic markers, controlled vocabulary (GO, KEGG, InterPro...)
• Tools for gene expression studies
• Tools for Chip-Seq data
• Integrative workflows and pipelines

Organizers:
Prof. M. Gonzalo Claros, Department of Molecular Biology and Biochemistry, University of Málaga, Spain.
Dr. Javier Pérez Florido, Bioinformatics Research Area, Fundación Progreso y Salud, Seville, Spain.
Dr. Francisco M. Ortuño, Bioinformatics Research Area, Fundación Progreso y Salud, Seville, Spain.

Motivation and Objectives.

Digital Twins is a very promising technique, as well as an ongoing research topic, imported from the Industry domain in order to develop Personalized Healthcare around the behavior of either patients’ disease or users’ health profile.

It is clear that the positive advance in the treatment of the diseases improve the quality of life. The World Health Organization (WHO) characterizes a healthy life first of all with the prevention of diseases and secondly, in the case of the presence of disease, with the ability to adapt and self-manage. Smart measurement of vital signs and of behavior can help to prevent diseases or to detect them before they become persistent. These signs are key to obtain individual data relevant to contribute to this understanding of healthy life. Here, the design of a Digital Twin appears in order to provides a frame of reference where to analyze the patient previously to the definitely treatment given by the doctor.

The objective of this session is to present and discuss the advances in this important topic, Digital Twins, in the generation of knowledge. We advocates that this session will proportionate an important meeting point among different and variate researchers.

Organizers: Prof. Dr. Cecilio Angulo

Prof. Cecilio Angulo is Full professor in the Automatic Control Department at UPC and Director of the Intelligent Data Science and Artificial Intelligence Research Center (IDEAI-UPC) where he is leading the Knowledge Engineering Research Group. Main topics of research includes cross-fertilization in the intertwine of Artificial Intelligence, Health and Industry, specially focused on social applications of them.

Universitat Politècnica de Catalunya. Intelligent Data Science and Artificial Intelligence Research Center, Jordi Girona 1-3, 08034 Barcelona, Spain

Prof. Dr. Juan Antonio Ortega

Prof. Juan Antonio Ortega is Full professor and obtained the Ph.D. degree in Computer Science in 2000 at the University of Seville in Spain. He is the Director of the Centre of Computer Scientific in Andalusia (Spain) www.cica.es and the head of the research group IDINFOR (TIC223) - Research, Development and Innovation on Computing Science. Our main research topics are: mobility, domotics and assisted systems, ubiquitous computing, time series and global information systems

University of Sevilla, ETS Ingeniería Informatica, Avda. Reina Mercedes s/n. Sevilla, Spain.

Prof. Dr. Luis González

Prof. Dr. Luis González is head of the researcher group SEJ 442 at University of Seville. His main research area is Machine Learning, Artificial Intelligence and Ubiquitous Computing with special focus on mobile devices, intelligent environments, e-Health services and telemedicine. His group is developing algorithms and devices for personalized and mobile health diagnostic support.

University of Sevilla, Department of Applied Economy I, Avda. Ramón y Cajal, 1. Sevilla, Spain

Motivation and Objectives.

Wide range of information could be obtained via imaging and spectral analysis of bio-origin samples and environmental conditions. Not only spectrometry, but also imaging is nowadays used for color analysis. The capability of sensors allows multispectral analysis, development of smart devices, and advanced analysis. The amount of measured datasets requires complicated mathematical models for features extraction, some could be performed by artificial intelligence, namely neural networks. The tasks consist of spectra evaluation, statistical analysis, comparisons, classification, etc.

In this special section should be provided discussion on novel development, implementation, and approaches in sensors, measurements, methods, evaluating software, and data mining focused on the spectral and color analysis. The topic should cover practical examples, strong results, and future visions.

Organizer: Dr. Jan Urban

Head of Laboratory of Signal and Image Processing, Institute of Complex Systems, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Faculty of Fisheries and Protection of Waters, University of South Bohemia, Czech Republic.

Motivation and Objectives.

Instruments and devices are almost similar and used for different scientific evaluations. They have become intelligent with the advancement in technology and by taking the help of artificial intelligence. In our daily life, sensors are corporate in several devices and applications for a better life. Such sensors as the tactile sensors are included in the touch screens and the computers’ touch pads. The input of these sensors is from the environment that converted into an electrical signal for further processing in the sensor system. The sensor’s main role is to measure a specific quantity and create a signal for interpretation.

Organizer: Prof. Dr. Barney

Intelligent instrumentation division, USA.

Motivation and Objectives.

Signal processing focuses on analysing, modifying and synthesizing signals such as sound, images and biological measurements. Signal processing techniques can be used to improve transmission, storage efficiency and subjective quality and to also emphasize or detect components of interest in a measured signal and is a very relevant topics in medicine.

Any signal transduced from a biological or medical source could be called a biosignal. The signal source could be at the molecular level, cell level, or a systemic or organ level. A wide variety of such signals are commonly encountered in the clinic, research laboratory, and sometimes even at home. Examples include the electrocardiogram (ECG), or electrical activity from the heart; speech signals; the electroencephalogram (EEG), or electrical activity from the brain; evoked potentials (EPs, i.e., auditory, visual, somatosensory, etc.), or electrical responses of the brain to specific peripheral stimulation; the electroneurogram, or field potentials from local regions in the brain; action potential signals from individual neurons or heart cells; the electromyogram (EMG), or electrical activity from the muscle; the electroretinogram from the eye; and so on.

In the other side, medical imaging is the technique and process of creating visual representations of the interior of a body for clinical analysis and medical intervention, as well as visual representation of the function of some organs or tissues (physiology). Medical imaging seeks to reveal internal structures hidden by the skin and bones, as well as to diagnose and treat disease. Medical imaging also establishes a database of normal anatomy and physiology to make it possible to identify abnormalities. Although imaging of removed organs and tissues can be performed for medical reasons, such procedures are usually considered part of pathology instead of medical imaging.

Organizer: Prof. Dr. L.Wang

Univ Calif San Diego, USA.

Motivation and Objectives.

Protein-protein interactions (PPI) refers to the association of proteins and the study of these associations from the perspectives of Biochemistry, signal transduction and protein interaction networks.The interactions between proteins are important in many biological processes.

PPIs have been studied with many methods and from different perspectives: biochemistry, quantum chemistry, molecular dynamics, signal transduction, among others. All this information enables the creation of large protein interaction networks – similar to metabolic or genetic/epigenetic networks – that empower the current knowledge on biochemical cascades and molecular etiology of disease, as well as the discovery of putative protein targets of therapeutic interest. Bioinformatic tools have been developed to simplify the difficult task of visualizing molecular interaction networks and complement them with other types of data. For instance, Cytoscape is an open-source software widely used and lots of plugins are currently available.Pajek software is advantageous for the visualization and analysis of very large networks.

Modulation of PPI is challenging and is receiving increasing attention by the scientific community. Several properties of PPI such as allosteric sites and hotspots, have been incorporated into drug-design strategies

Organizer: Prof. Dr. Yang

Univ Korea, South Korea.

Motivation and Objectives.

With continuous advancements of biomedical instruments and the associated ability to collect diverse types of valuable biological data, numerous recent research studies have been focusing on how to best extract useful information from the ‘Big biomedical Data’ currently available. While drug design has been one of the most essential areas of biomedical research, the drug design process for the most part has not fully benefited from the recent explosion growth of biological data and bioinformatics algorithms. With the incredible overhead associated with the traditional drug design process in terms of time and cost, new alternative methods, possibly based on computational approaches, are very much needed to propose innovative ways to propose effective drugs and new treatment options. Employing advanced computational tools for drug design and precision treatments has been the focus of many research studies in recent years. For example, drug repurposing has gained significant attention from biomedical researchers and pharmaceutical companies as an exciting new alternative for drug discovery that benefits from the computational approaches. This new development also promises to transform healthcare to focus more on individualized treatments, precision medicine and lower risks of harmful side effects. Other alternative drug design approaches that are based on analytical tools include the use of medicinal natural plants and herbs as well as using genetic data for developing multi-target drugs..

Keywords: Drug design, drug repositioning/repurposing, personalize medicine, data-driven healthcare, computational tools, Biomedical data analytics, Multi-target drugs.

Brief Bio. Hesham H. Ali is a Professor of Computer Science and Lee and Wilma Seemann Distinguished Dean of the College of Information Science and Technology at the University of Nebraska at Omaha (UNO). He also serves as the director of the UNO Bioinformatics Core Facility that supports a large number of biomedical research projects in Nebraska. He has published numerous articles in various IT areas including scheduling, distributed systems, data analytics, wireless networks, and Bioinformatics. He has also published two books in scheduling and graph algorithms, and several book chapters in Bioinformatics. He has been serving as the PI or Co-PI of several projects funded by NSF, NIH and Nebraska Research Initiative in the areas of data analytics, wireless networks and Bioinformatics. He has also been leading a Research Group that focuses on developing innovative computational approaches to model complex biomedical systems and analyze big bioinformatics data. The research group is currently developing several next generation big data analytics tools for mining various types of large-scale biological and medical data. This includes the development of new graph theoretic models for assembling short reads obtained from high throughput instruments, as well as employing a novel correlation networks approach for analyzing large heterogeneous biological and health data associated with various biomedical research areas, particularly projects associated with infectious diseases, microbiome studies and aging research. He has also been leading two projects for developing secure and energy-aware wireless infrastructure to address tracking and monitoring problems in medical environments, particularly to study mobility profiling for advancing personalized healthcare

Organizer: Prof. Hesham H. Ali

UNO Bioinformatics Core Facility. College of Information Science and Technology. University of Nebraska at Omaha.

Motivation and Objectives.

RNAs play a wide range of functions in a variety of cellular processes and in disease mechanisms, through their informational roles and also by their ability to recognize and bind target molecules, proteins, and other nucleic acids. RNAs, including microRNAs, long non-coding RNAs, and circRNAs are highly pleiotropic molecules with regulatory roles in complex networks. The special session will be dedicated to all the aspects of RNA study by computational and bioinformatics methods, including systems biology and multi-omics strategies to characterize RNA expression, interactions and functions. Specifically, but not exhaustively, contributions on these topics are encouraged: the most recent acquisition and tools for data manipulation; integrative approaches; data reproducibility.

Organizers: Prof. Stefania Bortoluzzi

Prof. Stefania Bortoluzzi (PhD) is associate professor of Applied Biology at the Department of Molecular Medicine of the University of Padova (Italy). She leads a Computational Genomics Group working in the fields of bioinformatics and systems biology applied to the study of genome and transcriptome variation in cancer and disease, with an intense focus on the roles of microRNAs, other non-canonical small RNAs and circular RNAs in haematological malignancies. Member of Non-Coding RNA and High-throughput journals Editorial board. Stefania Bortoluzzi, Department of Molecular Medicine, University of Padova Via G. Colombo, 3 - 35131, Padova, Italy Phone +39 049 827 6502 Fax +39 049 827 6209 Email: stefania.bortoluzzi@unipd.it

Dr. Luca Agnelli (senior researcher)

Luca Agnelli (PhD) is a senior researcher at the Department of Oncology and Hemato-oncology of the University of Milan (Italy). He is mainly, but not exclusively, involved in bioinformatics and biostatistics research in the field of B- and T-cell tumors, with particular focus on non-coding transcriptome. Member of Non-Coding RNA journal Editorial board. Luca Agnelli, Department of Oncology and Hemato-oncology, University of Milan F. Sforza, 35 - 20122 Milan (IT) phone +390255033328 fax +390255034571 Email: luca.agnelli@unimi.it