Next Generation Sequencing (NGS) is a broadly used term to describe the most recent sequencing technologies, including Illumina, Roche/454, Ion Torrent, SOLiD and Pacific Biosciences. These technologies allow the quick and cost-effective sequencing of DNA and RNA, opening new ways for the study of genomics, transcriptomics, gene expression, and systems biology, among others.

The continuous improvements on those technologies (longer read length, lesser base calling errors, greater throughput, etc.) and the broad application of NGS in many research fields, is producing a continuous increase of data requiring improved bioinformatics tools. Therefore, we invite authors to submit original research, pipelines and review articles on topics helping in the study of NGS data, such as (but not limited to):

• Tools for data pre-processing (quality control and filtering).
• Tools for sequence mapping.
• Tools for de novo assembly.
• Tools for quality check of sequence assembling.
• Tools for the analysis of genomic data: identification and annotation of genomic variants (variant calling, variant annotation).
• Tools for functional annotation: identification of domains, orthologues, genetic markers, controlled vocabulary (GO, KEGG, InterPro,...)
• Tools for biological enrichment in non-model organisms.
• Tools for the analysis of transcriptomic data: RNA-Seq analyses (quantification, normalisation, filtering, differential expression) and distinguishing transcripts, alleles and paralogs.
• Tools for Chip-Seq data.
• Tools for “big-data” analyses.
• Tools for handling and editing complex workflows and pipelines.

Motivation: For a proper description of the dynamic phenomenon it is necessary to discriminate between the trajectory of the evolution towards the limit set and the properties of the limit set. The limit set is the final state which may be dynamic, i.e. oscillating or following the trajectory of deterministic chaos. Concrete examples relevant to the proposed session are, for example, the living cycle of one living organism from the connection of gametes to the death - this is the trajectory of evolution of an in part discrete self-organised system - or behaviour of the unconstrained fish shoal in the free space - this is possible to assess a limit set. Structured systems on the trajectory to the limit set prevail in the Nature.

Objectives: The objective of the session is to gather researchers active in the discrete dynamic systems research, i.e. multilevel cellular automata or agent - based models, researchers in qualitative dynamics and the relevant experimentalists, namely behavioural science researchers, cell dynamic researchers etc. Experimenters on relevant model systems such as chemical self-organisation are also welcome. Such meetings occur only seldom and are never balanced in attendance, often producers of primary datasets do not receive sufficient audience.

The session should contribute to answering following questions:

• Which primary time and space element predicted by the dynamic model.
• Which are the experimental limits of behavioural and cell dynamic experiment and how well they might reproduce model predictions.

Only merging of these two aspects may give the answer on proper setting and interpretation of biological measurement.

The experimental results interpretation depends proper evaluation of the measured data, their comparison and classification. There becomes into importance also the experimental setup, conditions, and measurement device attributes. The significance of the interpretation could be optimized via experimental design. The collection of all settings requires approach of catalogization, and protocol database. In this way, there could be emphasizes of the requirements necessary for the obtaining the best possible information, in the maximal relevant content to assure the nonbiased interpretation and knowledge extraction. There are, of course, specific details presented in the bioinformatical cases. On the other, there were already solved methods in different fields, which could serve in several bioinformatic cases as well.

In this special section we will describe broad examples from experimental design through information tuning and data standardization to real implementation using optical sensors, image processing and analysis, and distributed knowledge database. The aim of this section is to present the possible increase of the data interpretation and the related methods.

Over the past three decades, the predominant paradigm in drug discovery was designing selective ligands for a specific target to avoid unwanted side effects. However, in the last 5 years, the aim has shifted to take into account the biological network in which they interact. Quantitative and Systems Pharmacology (QSP) is a new paradigm that aims to understand how drugs modulate cellular networks in space and time, in order to predict drug targets and their role in human pathophysiology.

The goal of this symposium is to go trough the current computational and experimental QSP approaches such as polypharmacology techniques combined with systems biology information and consider the use of new tools and ideas in a wider 'systems-level' context in order to design new drugs with improved efficacy and fewer unwanted off-target effects.

The use of network biology produces valuable information such as new indications for approved drugs, drug-drug interactions, proteins-drug side effects and pathways-gene associations. However, we are still far from the aim of QSP, both because of the huge effort needed to model precisely biological network models and the limited accuracy that we are able to reach with those. Hence, moving from 'one molecule for one target to give one therapeutic effect' to the 'big systems-based picture' seems obvious moving forward although whether our current tools are sufficient for such a step is still under debate. We will discuss all these issues in this symposium.

The goal of this special session is to explore the use of emerging parallel computing architectures as well as high performance computing systems (Supercomputers, Clusters, Grids) for the simulation of relevant biological systems in the context of Structural Bioinformatics, Computational Biology and Computational Chemistry. We welcome papers, not submitted elsewhere for review, with a focus in topics of interest on:

• Programming Models and Systems for Multicore, Manycore, and Clusters of Multicore/Manycore.
• Parallel Stochastic Simulation
• Biological and Numerical Parallel Computing
• Parallel and Distributed Architectures
• Emerging Processing Architectures (e.g. GPUs, Intel Xeon Phi, FPGAs, mixed CPU-GPU or CPU-FPGA, etc)
• Parallel Model Checking Techniques
• Parallel Algorithms for Biological Analysis
• Cluster and Grid Deployment for System Biology
• Soft Computing Algorithms in Bioinformatics, Computational Biology and Computational Chemistry
• Application of HPC Developments in Structural Bioinformatics, Computational Biology and Computational Chemistry
• Biological and Chemical databases for Big Data Management
• Automated Verification in Computational Biology
• System Infrastructure for High Throughput Analysis
• Biomolecular Structure Prediction and Large Molecular Systems
• Molecular Visualization of Biological Big Data
• Large Scale Proteomics

We welcome research papers, not submitted elsewhere for review, with a focus in topics of interest ranging from but not limited to:

• Target identification and validation.
• Computational Chemistry: Modelling biological processes through Quantum Chemistry and hybrid QM:MM approaches, Interpreting Ligand-Protein binding sites with novel non-covalent interactions analysis, Applying density functional theory (DFT) for predicting drug reactivity towards protein fragments and DNA, computing excited states to disclose the in vivo action of DNA/sensitizers and related molecules.
• Chemoinformatics: Methodological basis and applications to drug discovery of: QSAR, Docking, CoMFA-like methods, High-performance Computing (HPC), Cloud Computing, Biostatistics, Artificial Intelligence (AI), Machine Learning (ML), and Bio-inspired Algorithms like Artificial Neural Networks (ANN), Genetic Algorithms, or Swarm Intelligence.
• Multidimensional QSAR. Applications and recent advances in QSAR concepts exploring higher dimensions related with their benefit in the drug-discovery process.
• Bioinformatics & Biosystems: Methodological basis and applications to drug design, target or biomarkers discovery of: Alignment tools, Pathway analysis, Complex Networks, Non-linear methods, Microarray analysis, Software and Web servers.
• High Throughput Screening (HTS) of drugs; Fragment Based Drug Discovery; Combinatorial chemistry and synthesis.

Most prevalent diseases are partly caused or aggravated by lifestyle choices that people make in their everyday life. Accordingly, there exist an urgent need for mechanisms to automatically and autonomously identify and eventually change people's unhealthy behaviors. This special session aims at showcasing the latest achievements in the monitoring, analysis and understanding of human behavior through smart technologies. We welcome novel, innovative, and exciting contributions in areas including but not limited to:

• Applications for cognitive and physical health
• Ambient assisted living applications
• Smart coaching systems
• Mobile social networks
• Behavioral grouping
• Participatory sensing (crowd-sensing)
• Behavior analysis for alerts and recommendations
• Behavior sensing and personalization of mobile devices
• Context-awareness and semantic modeling
• Affective computing (emotion recognition)
• Activity and action recognition
• User mobility modeling (location tracking)
• User-centric computing
• Benchmarking, databases and simulation tools

The biological sciences are quickly becoming data-centered sciences and, as a result, they are, more than ever, one of the key targets for data scientists, particularly from the viewpoints of Pattern Recognition (PR) and Machine Learning (ML)

Nowhere else this is more evident than in the -omics sciences, spanning the fields of genomics, proteomics, metabolomics and transcriptomics. In all of these, the advances in data acquisition are creating a true deluge of information and, with it, new challenging scenarios related to data management in all forms, compounded by privacy and legal issues.

In this scenario, PR and ML methods hold the promise of opening new avenues for transforming raw and unstructured -omics information into usable knowledge for the biomedical and bioinformatics domains.

Topics that are of interest to this session include (but are not necessarily limited to):

• Applications of PR and ML methods to problems in the -omics sciences (including genomics, proteomics, metabolomics and transcriptomics).
• Development of novel PR and ML methods suitable for application to -omics problems.
• PR and ML-based methods for decision support in the -omics sciences.
• PR and ML for data processing, preparation and transformation in -omics.
• Scalable PR and ML models for Big Data problems in -omics, including online and stream learning, as well as parallel and high-performance computing approaches.

More information at

http://www.cs.upc.edu/~avellido/research/conferences/IWBBIO16-PRML-Omics.html

From dealing with the complex storage and accessibility requirements, to the challenge of organizing and extracting meaningful information from Big Data, resources have a key role in today's research workflows. Bioinformatics support involves very different domains: from the creation of standards and rules to enable data exchange and representation to the maintenance of sustainable and efficient hardware and software infrastructures where data can be hosted and analysed. Although recognized by the research community, this support role does not often find a devoted discussion forum in scientific events.

In this special session we want to provide an opportunity to share the latest ideas and developments on how different resources provide service to bioinformatics research. We welcome contributions focused on all aspects of bioinformatics and biomedicine support, roughly divided in the following topics:

• Data providers: Creating and maintaining databases hosting organized data enabling research involves some serious issues, from raw data hosting to curation and organization of the information to enable users' accessibility.
• Tool development: Analysing and integrating data needs for the creation of tools and algorithms that help users make sense of the current overflow of information.
• Computing and infrastructure: Data organization and analysis is not possible without specific infrastructure and technical support enabling storage and accessibility, while ensuring sustainability and scalability.
• Standards and integration: Information integration is one of the most demanding challenges we face in bioinformatics research. Developing standards and common guidelines is the way forward to eliminate current barriers for data exchange and re-use.

The motivation of this special session arises from the limitations caused by neuromotor disorders in the fundamental areas of human being: mobility, communication, manipulation, orientation and cognition. This special session will collect publications about the newest advances and trends in Assistive Technologies for people with motor disorders. The term motor disorder includes some pathologies with some common patterns as spinal cord injury, cerebral palsy and stroke.

According to the Association for the Advancement of Assistive technology in Europe (AAATE) the Assistive Technology (AT) is any item, piece of equipment, or product system, whether acquired commercially off the shelf, modified, or customized, that is used to increase, maintain, or improve functional capabilities of children with disabilities. AT is used in the context of the whole life of a person with a disability, to function as a part of an individual's total system for support, and not just in one role, setting, or functional application.

AT frequently uses methods and knowledge developed in other technological (Robotics, Informatics, Telecommunications, Artificial Intelligence, etc.,) or humanistic (Psychology, Pedagogy, Sociology, etc.,) fields. The main objective of AT (equipments and services) is to contribute to a better quality of life of the many persons affected by disabilities worldwide, through the integration of technological aspects in equipments, services and contexts.

These technologies must be adapted to the special features of the users affected by disabilities. Human-Computer Interaction, for instance, can contribute significantly to Assistive Technology. Rehabilitation robotics is also an emerging field focused on recovering physical and cognitive skills.

Tha main topics of this special session will be:

• Mobility and manipulation technical aids.
• Human-computer interaction.
• Rehabilitation robotics.
• Physiological sensors.
• Biofeedback and Virtual Reality.

In the last 20 years many resources have been spent in experimentation and marketing of telemedicine systems, but - as pointed by several researchers - no real product has been fully realized - neither in developed or in underdeveloped countries. Many factors could be detected:

• lack of a decision support system in analyzing collected data;
• the difficulty of using the specific monitoring devices;
• the caution of patients and/or doctors towards e-health or telemedicine systems;
• the passive role imposed to the patient by the majority of experimented systems;
• the limits of profit-driven outcome measures;
• a lack of involvement of patients and their families as well as an absence of research on the consequences in the patient's life.

The constant improvement of ICT tools should be taken into account: at-home and mobile monitoring are both possible; virtual visits can be seen as a new way to perform an easier and more accepted style of patient-doctor communication (which is the basis of a new active role of patients in monitoring symptoms and evolution of the disease). The sharing of this new approach could be extended from patients to healthy people, obtaining tools for a real preventive medicine: a large amount of data could be gained, stored and analyzed outside the sanitary structures, contributing to a low-cost approach to health.

The goal of this session is to bring together interdisciplinary experts to develop (discuss about) these topics:

• decision support systems for the analysis of collected data;
• customised monitoring based on the acuteness of the disease;
• integration of collected data with e-Health systems;
• attitudes of doctors and sanitary staff;
• patient-doctor communication;
• involvement of patients and of their relatives and care-givers;
• digital divide as an obstacle / hindrance;
• alternative measurements on the effectiveness of telemedicine (quality of life of patients and care-givers, etc)
• mobile vs home monitoring (sensors, signal transmissions, etc)

Since the design of sterilization department is one of the most sophisticated and complex sections inside healthcare facilities and hospitals, creation this department is very important task. Sterilization department should satisfy some special requirements and conditions to comply with infection control. These conditions reflect the department space area, department location inside the hospitals, function relation towards the operating rooms department and Intensive care unit, furthermore devices capacities. In this paper, we will introduce the minimum requirements and needs from location selection, minimum required area, device capacities and how to comply with the quality and infection control. These requirements have been applied to many hospitals and centers and we have recorded some improvements and enhancements for work flow and infection control.

Sequence Modeling is one of the most important problems in bioinformatics. In the sequential data modeling, the computational algorithms can be used to modeling and comparing the biological sequences. Hidden Markov Models(HMMs) have been widely used to find similarity between sequences, since the performance of HMMs are suitable for handling of sequence patterns with various lengths. Some of the most important topics in this session are:

• Modeling of biological sequences in bioinformatics;
• The application of Hidden Markov Models(HMM);
• HMM in modeling of sequential data;
• The advantages of HMM in biological sequence modeling in compare of other algorithms;
• The new algorithms of training HMM;
• Gene sequence modeling with HMM;

The challenge of handling big data is considered as one of the main hot topics that concerns most organizations especially in the medical sector. Nowadays, the usage of information systems and strategic tools have been applied to various fields. Through time a vast amount of data is generated. Although there are several data processing to extract knowledge and various visualization tools to present these data, the overarching challenge of the current big data paradigm is encourage researchers to develop novel data processing and computational algorithms. Furthermore securing these data still a challenge that runs competitions to develop and applying a number of new promising security algorithms.

The aim of this special session is to bring scientists, researcher scholars, and students from academia and industry to present recent and ongoing research activities about the recent advances and techniques of Securing data and applying Optimization techniques especially in medical applications and to allow the exchange and share of proposed ideas and algorithms experiences. Topics of interest include but are not limited to:

• Big data analytics modeling.
• Bioinformatics and Biomedical Applications.
• Data Mining and Knowledge Representation.
• Machine learning for medical data analysis.
• Information Security and Biometrics.
• Supervised and Unsupervised learning of Big Data.
• IOT applications.
• Optimization Algorithms.

More information at:

Information Security Optimization and Big Data (ISOBD)