• Generalife Palace
  • Alhambra View
  • Alhambra's Night
  • Granada's Panoramic (I)
  • Granada's Panoramic (II)
  • Granada's Cathedral
  • Moorish Windows
  • Court of the Lions
  • Costa Tropical of Granada
Generalife Palace1 Alhambra View2 Alhambra's Night3 Granada's Panoramic (I)4 Granada's Panoramic (II)5 Granada's Cathedral6 Moorish Windows7 Court of the Lions8 Costa Tropical of Granada9
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Special Session Proposals

SS1 Multi-biomarker and informatics in cancer diagnosis

The session will discuss the join research between Hospital Doctors and Informatic Scientists. With the development of life science, the clinical laboratory could provide much more test for patients than before, currently this use reference interval or cut off values as clinical diagnostic standred which could not significantly improve the specificity and sensitivity simultaneously. If the informatic tools could be used to combined analysis multiple clinical test and biomarkers, it will be enhance the using of clinical information from medical laboratory and also could stimulate the translational medicine studies of "omic" technology and theory.

Dr. Prof. Yaping Tian
, Department of Clinical Biochemistry, Chinese PLA General Hospital, Beijing (China).
SS2 Discovery of non-coding and structured RNAs

Non-coding (nc)RNAs are emerging as some of the most versatile and important biological molecules in the cell. They can act both in cis and in trans to mediate functions as diverse as catalysis, metabolite sensing, regulation of gene expression, epigenetics, chromatin stability, splicing, and more. The explosion of RNA sequences generated by next-gen sequencing and accumulating in various databases represents a massive, and relatively un-explored, "New World" of ncRNAs. The identification of novel ncRNAs from these data is a crucial, but challenging, problem for bioinformatics. Many ncRNAs require that they fold into thermodynamically stable RNA structures to carry out their functions. If these functions are evolutionarily conserved, then structures may also be conserved between related sequences. Thus, identifying thermodynamically stable and conserved RNA structures from sequence data can help identify putative ncRNAs. This session will cover various approaches for modeling RNA structures using thermodynamics, biochemistry, and sequence comparison, identifying homologous RNA sequences/structures, and using these methods to suggest which sequences have likely non-coding functions. This session will also cover the application of these methods to identify ncRNAs in target species.

Dr. Walter N. Moss
, Yale University and Howard Hughes Medical Institute, New Haven (USA).
SS3 Biological Knowledge Visualization

Biotechnology produces large amounts of data, to be handled and analyzed by computational methods. The scale and complexity of such input data, but also of the analysis results, is large, and can be tackled by visual techniques for representation and interpretation. The focus of this special session is the discussion of approaches that integrate visual intelligence into the analytical process of such biological data. Contributions may range from the development of novel visual techniques to the successful application of existing ones in biological or biomedical studies.

Dr. Rodrigo Santamaria
, University of Salamanca (Spain).
SS4 High Performance Computing in Bioinformatics

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 and for applications in Bioinformatics, Computational Biology and Computational Chemistry. We welcome papers, not submitted elsewhere for review, with a focus in topics of interest ranging from but not limited to:
  • 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.
  • Biologically inspired algorithms.

Dr. Horacio Perez-Sanchez
and Dr. Jose M. Cecilia, Catholic University of Murcia (UCAM), (Spain).
Dr. Ivan Merelli, Institute for Biomedical Technologies, National Research Council of Italy, Milano (Italy).
SS5 Mathematical and computational approaches for protein folding prediction

Proteins, formed by a string of amino acids folding into a specific tridimentional shape, carry out the majority of functionality within an organism. However, simulating with accuracy the folding process occurring in reality remains a very difficult task, as forces involved in the stability of the proteins conformations are currently not perfectly modeled, and due to an astronomically large number of possible 3D structures, among other things. This special session aims to discover new trends and investigative directions in the 3D protein structure prediction (PSP) problem, encompassing both mathematical, physical, computer science, and molecular biology aspects involved in this field. Researchers in all of these disciplines, interesting by challenges raised by the PSP problem, are thus welcome to submit original papers in topics related to this problems, ranging from but not limited to:
  • Theoretical and practical aspects of protein folding.
  • New trends and discoveries in self-avoiding walks.
  • Biophysics of protein folding.
  • New artificial intelligence trends for PSP software.
  • Biological aspects of protein folding.
  • Mathematical study of folding dynamics.
  • Complexity of the PSP problem.

Dr. Christophe Guyeux
, IUT Belfort-Montbeliard, Department d'Informatique, Belfort (France).
SS6 ePathology - Realities and Perspectives

The session will discuss the current research and ongoing activities implemented in the field of ePathology. Digital imaging as well as virtual pathology boards acquire more and more importance. Application of medical and laboratory information management systems for pathology purposes ia also important and actual. Special importance acquires implementation of eLearning technologies for continuous medical education of pathologists as well as introduction and practical application for realization of quality assurance programs in pathology and cytology.

Dr. Ekaterine Kldiashvili
, Georgian Telemedicine Union (Association), Tbilisi (Georgia).
SS7 Modelling of cellular pathways and disease

This session will discuss applications of mathematical and computational techniques to the representation of biological processes or pathways, with the aim of gaining a mechanistic understanding of cellular functions. A wide range of approaches will be considered, ranging from qualitative network representation to fully quantitative kinetic models. Applications may focus on a specific metabolic, signalling and regulatory pathway, or on the contrary offer genome-scale coverage of processes implicated in a particular biological function or disease. We welcome interdisciplinary papers presenting the integration of modelling techniques with experimental analyses.

Dr Jean-Marc Schwartz
, Faculty of Life Sciences, University of Manchester (UK).
Prof Marija Krstic-Demonacos, School of Environment & Life Sciences, University of Salford (UK).
SS8 Integration of data, methods and tools in biosciences

With the rise of biotechnology and bioinformatics, a number of problems regarding storing, searching and using biological data occur. The data are scattered over a large number of repositories (public or private) and stored in a large number of different formats. Furthermore, some formats are not adequate for automatic computer processing (such as text documents) and require some kind of preprocessing before they can be input into computer algorithms. This situation makes searching and analyzing the data very difficult, leaving facts and knowledge on observed biological phenomena hidden in databases and digital collections.

The above problems and other similar problems can be overcome only by an integrative bioinformatics approach. The integration can be done across different aspects and on various levels. Topics of interests include (but are not limited to):
  • database integration techniques,
  • data acquisition from heterogeneous sources,
  • genotype-phenotype associations researches,
  • integrative modeling and analysis of processes and systems in biosciences,
  • tool integration and workflow systems,
  • computational infrastructure for biological researches, including laboratory management systems,
  • biological ontologies and metadata,
  • integrative data and text mining approaches.
Contributions that addresses any other aspect of integrating data, methods, techniques and/or tools, are also welcome.

Dr. Vesna Pajic
, University of Belgrade, Faculty of Agriculture (Serbia).
SS9 Biomaterials in Biomedicine: Computational approaches

The development of materials that can successfully replace biological tissues both in function and appearance, the so-called Biomaterials, is a field of growing interest in Biomedicine. The use of computational methods to determine or predict the physical properties of these materials has become one of the main focuses of the latest research in this area, allowing pre-clinical non-invasive methods for evaluation and testing of this type of materials. Also, theoretical modelling of these materials can expedite research by allowing conducting simulated experiments in order to find the solution in the real system that is being studied in response to changing conditions, and helps obtaining information on optical, mechanical and many other potentially interesting properties.
The main topics of interest of this Special Session include (but are not limited to):
  • Computational methods for assessment and prediction of physical (including mechanical, optical,...) properties of biomaterials;
  • Application of biomaterials in Biomedicine;
  • Modelling systems of biomaterials;
  • Software tools and simulation packages for the evaluation of suitability of biomaterials;
Dr. Razvan Ghinea
, Department of Optics, University of Granada (Spain).
Dr. Luis Javier Herrera, Department of Computer Architecture and Computer Technology, University of Granada (Spain).
Dr. Maria del Mar Perez, Department of Optics, University of Granada (Spain).
SS10 Effective Soft Computing Methods for Biomedical Signals

The goal of this special session is to elaborate applications of soft computing methods for biomedical signals such as ECG, EMG, and EEG. This session will discuss new hybrid algorithms and investigate effective as well as high performance computing techniques for the classification of biomedical signals for diagnosis or the other applications in Biomedical Engineering and Bioinformatics. We welcome papers, not submitted elsewhere for review, with a focus in topics of interest ranging from but not limited to:
  • Artificial Neural Networks Algorithms on Biomedical Signals.
  • Fuzzy Systems and Fuzzy Clustering Algorithms on Biomedical Signals.
  • Probabilistic Model Algorithms on Biomedical Signals.
  • Metaheuristic Algorithms on Biomedical Signals.
  • Hybrid Algorithms on Biomedical Signals.
Prof. Dr. Bekir KARLIK
, Faculty of Engineering, Selcuk University, Konya, (Turkey)
SS11 Chaperone Therapy for Protein Misfolding Disorders with Brain Dysfunction

Chaperone therapy is a new concept of molecular therapeutic approach, first developed for lysosomal diseases, based on a paradoxical molecular phenomenon involving lysosomal enzyme proteins and their competitive inhibitors as intracellular enhancers (chaperones). The misfolded mutant enzyme protein is stabilized as a molecular complex with its substrate analogue, chaperone, and transported safely to the lysosome. The complex is automatically dissociated in the lysosome under the acidic condition, the free mutant protein remains stable, and the enzyme activity is expressed. The small chaperone molecule has been confirmed to be delivered to the brain tissue through the blood-brain barrier.

This new trial was targeted initially at a few lysosomal diseases, and then has been expanded to many other diseases with pathological protein dysfunction due to structural misfolding. The advantages of this molecular approach over other currently available therapies for genetic and protein misfolding diseases are summarized twofold; first, oral administration to individuals with intractable diseases; and second, delivery to the central nervous system for therapy of brain diseases currently not available with other experimental or clinical trials. In this session we discuss the present status of chaperone therapy research, focusing on chemical compounds, enzyme-chaperone interactions, and animal and human experiments for a few genetic diseases. This therapeutic approach will become a novel and revolutionary scientific and medical strategy in the near future.

Dr. Yoshiyuki Suzuki
, Tokyo Metropolitan Institute of Medical Science (Japan).
SS12 Error models, Sources and Statistical Biases in Next Generation Sequencing

Motivations and objectives: Next generation sequencing (NGS) is an important technology for today's biomedical research. The growing importance of NGS for the clear understanding of various biological systems has induced a competition among several companies, each trying to come up with a sequencing platform which can produce high quality longer read sequences with greater throughput and reduced cost. However, whole genome sequencing is accompanied by higher error rates than capillary sequencing.

There is considerable amount of evidence about context dependency and other systematic errors across different NGS platforms and different releases of same technologies now. The sources of systematic errors are extremely diverse. The error sources range from library preparations, hardware and software artefacts, up to DNA/RNA error-prone patterns, secondary structure and genome function.

In order to make Bioinformatic and Biomedical community aware of well known and newly developed systematic errors in NGS (which could negatively affect their research and clinics) we announce this Special Issue on 'Error models, sources and statistical biases in Next Generation Sequencing'. We invite authors to submit original research, software application and review articles on above topic, including the following:

  • Typical systematic biases across different NGS platforms, including methods to correct for them.
  • Different NGS experimental techniques: DNA_seq, RNA_seq, CHiP_seq etc, and error sources within them.
  • NGS data analysis tools: aligners, assemblers, base callers, SNP-callers. Their impact into statistical error biases.
  • Particular cases of NGS applications to Biology, Genetics and Medicine, which are known (or may be) to be affected by systematic sequencing errors, such as GWAS etc.
  • Hybrid Algorithms on Biomedical Signals.

Dr Irina Abnizova
, Sequence Informatics team, Wellcome Trust Sanger Institute, Welcome Trust Genome Campus (UK).
SS13 Computational analysis of gene regulatory elements with next-gen sequencing data

The advent of next-generation sequencing (NGS)-based epigenetic profiling assays opens new perspectives for studying gene regulation. In particular, ChIP-Seq against histone marks and transcription factors (TFs), BS-Seq for DNA-methylation profiling and various protocols for assessing chromatin accessibility allow for a detailed characterization of the chromatin states of tens of thousands of cis-regulatory elements at once. Moreover, high-throughput protocols for sequencing RNA 5'ends allow for genome-wide monitoring of transcription initiation events at single base pair resolution. This session focuses on novel computational approaches to extract insights on gene regulatory mechanism from the vast amounts of epigenetic profiling data that have been accumulated over the last few years. We welcome contributions on topics ranging from but not limited to:
  • Promoter inference and classification from transcript mapping data.
  • Functional classification of regulatory elements based on chromatin features.
  • Methods for identifying differentially modified chromatin regions.
  • Prediction of nucleosome positioning from DNA sequence and TF binding events
  • Discovery of genetic variants associated with changes in chromatin state.
  • Usage of epigenetic profiling data for medical diagnosis and treatment decision

Dr. Philipp Bucher
, Swiss Federal Institute of Technology in Lausanne (EPFL) (Switzerland).
SS14 Better Oncology Treatment and Patient Outcomes by Using Therapy-Related Symptom Checklists (TRSC/TRSC-C) and a Computerized Two-Way Communication System

This special session will describe and illustrate the development/measurement properties, current use, and future electronic uses of patient-friendly symptom checklists for adults (TRSC) and children (TRSC-C) oncology patients. These checklists can be completed in less than 5 minutes by adults and children/parents, and involve no radical alterations in or increased costs of clinical practice. The adult checklist was developed 1984-1995 and the child checklist 2004-2010. Both checklists now have versions in English, Spanish, Thai, Pilipino, Chinese, and Bahasa Indonesia, and have been used in clinic settings in the USA and other countries.

The checklists were originally developed to reduce observed under-documentation of treatment symptoms of concern to patients in medical records. The hope was that use of these checklists (25 symptoms for adults and 30 for children) would lead to better documentation through integration of the checklists into electronic medical records (EMR), enhance communications among patients and clinicians, and improve health outcomes. Completed research has found high levels of patient/clinician satisfaction with use of the TRSC, no increase in clinic costs, and strong correlations of TRSC/TRSC-C scores with the number of patient symptoms documented and managed, patient functional status, and patient quality of life, A recently published sequential cohort trial with adult outpatients at a Mayo Clinic Health System community cancer center reported that use of the TRSC produced a 7.2% higher covariate adjusted patient quality of life, 116% more symptoms documented and managed, and higher functional status. These results were statistically and substantively significant.

This special session will illustrate transitions among design, measurement, application, and informatics required for good patient care. Audience participation will be solicited, and establishment of relationships among the audience for work along the lines presented and discussed in this special session will be encouraged

Dr. Arthur R. Williams
, Research Associate, CINDRR, US Department of Veterans Affairs, and Professor, Department of Healthcare Policy and Management, College of Public Health, University of South Florida, Tampa (USA)

Dr. Phoebe D. Williams
, Professor, School of Nursing, Kansas University Medical Center, Kansas City, Kansas (USA)
SS15 Computational MRI: Theory, Dynamics and Applications

Computational techniques are invaluable to the continued success and development of Magnetic Resonance Imaging (MRI) and to its widespread applications. New processing methods are essential for addressing issues at each stage of MRI techniques. Magnetic Resonance Imaging simulations based on the Bloch NMR equations are of high educational value. They serve as essential tools in basic MRI method development, sequence design and protocol optimization. In this special session, the underlying physical and biomedical models of the Bloch NMR flow equations, their field of applications and possible limitations will be discussed. Magnetization preparation will be simulated in order to tailor sequence protocols for specific applications, exploiting basic spin relaxation as well as advanced Magnetic Resonance contrast mechanisms such as flow and diffusion. The main objective of this special session is to bring together the mathematicians, computer scientists, theoretical physicists, medical scientists and the engineer and apply their tools through high quality paper presentations and contribute to this fast developing and most exciting field of our time without acquiring the most sophisticated equipment. Volume I of a new book titled "Theory, Dynamics and Applications of MRI" will be released and presented at this special session. The book is intended to present basic theory of MRI and develop several fundamental equations which can be invaluable for quantitative and qualitative analysis of NMR magnetizations and signals. Based on this special session, scientists should be able to apply basic MRI methods to solve real life problems using computational methods of their choice.

Dr. Omotayo Bamidele Awojoyogbe
, Department of Physics, Federal University of Technology, Minna, Niger-State (Nigeria)
SS16 Bioinformatical Approaches to Disordered Proteins

According to the "structure-function-paradigm" a stable, folded structure is a pre-requisite of protein function. However, since the turn of the century it became evident via an increasing number of known examples that many proteins are able to serve crucial functions in vivo without adopting a well-defined 3D structure. In accordance with the typical functions these Intrinsically Unstructured/Disordered Proteins (IUPs/IDPs) serve in signalling, regulation and transcription, they were found to be at the heart of many diseases such as cancer, neurodegenerative diseases and diabetes, among others. This sparked interest in the focused research of IUPs not only at a basic science level but also in biomedicine/pharmacology.

However, due to biological and technical reasons, experimental study of these proteins remains difficult and expensive and therefore the exact biological function, mode of action and biophysical/thermodynamical description of the majority of IUPs remain elusive. Because of these difficulties, bioinformatics tools that target protein disorder play an important role in the identification and characterization of IDPs. This is exemplified by the fact that the majority of our systems-, network- and evolutionary level knowledge of IUPs are based in various bioinformatics prediction methods and analyses.

In this session we present the concept of IUPs and focus on the current, state-of-the art bioinformatics approaches, tools and results of analyses concerning protein disorder.

Prof. Istvan Simon
, Istitute of Enzymology, Research Centre for Natural Sciences (Hungary)
SS17 Annotation and Curation of Uncharacterized Proteins: Systems Biology Approaches

A hypothetical protein (HPs) is a protein whose existence is predicted but whether or not it is expressed remains uncertain. However, many HPs in the recent past have been known to be expressed in vivo. With various methods known to identify components in cell membrane, the functional significance of thousands of proteins especially those that do not have function, not expressed, unique or common among genomes is least understood. Apart from this, many HPs might turn out to be pseudogenes at a later point of time and the use of these proteins remain mis-conducive. To circumvent the problem, several methods to easily screen functional candidates among many hypothetical proteins, use of feature selection algorithms and testing the efficacy of these proteins in terms of precision and accuracy using stochases have widely been covered. With experimental procedures for HP function prediction being low throughput by nature, there has been a need to precisely know their functions for a better understanding of the underlying biological mechanism. We would invite authors interested in these niche areas of annotating uncharacterized proteins and functional genomics for their contribution in any of the following areas, not just limited to the following but to a broader purview:
  • Computational flow for the functional annotation of uncharacterized proteins using motif discovery, sequence and structural similarity, structural homology, hypothome (interactome of hypothetical proteins) or combination of data from highly similar non-interacting proteins (Similactors).
  • Predictive approaches based on Gene Ontology (GO).
  • Feature selection and machine learning methods.
  • Diseasome approaches.
Prof. Alfredo Benso
, Department of Control and Computer Engineering, Politecnico di Torino (Italy)

Dr. Prashanth Suravajhala
, Founder of Bioclues.org and Director of Bioinformatics.org
SS18 Stochastic Modelling of Biological Systems

Recently there has been a significant interest in the stochastic approach for modelling biological systems, mainly because experimental data are providing evidences that random events play significant roles in determining the complex behaviours observed in living organisms. The growing amount of evidences arising from experimental observations at the single cell level are showing that fundamental biological processes such as, e.g., fate decision making, gene expression regulation, phenotypic variability are deeply conditioned by random fluctuations at the molecular level.

Approaches grounding on computational stochastic modelling and simulations are proving to be useful tools for gaining insights about the role played by random events in determining the global dynamics of biological networks. In these cases deterministic descriptions fail both in predicting the observed random fluctuations and in capturing stochastic-driven phenomena such as stochastic focusing, stochastic switching and multiplicative noise effects. The most popular strategy for building stochastic models of biological phenomena consist in describing the temporal evolution of the considered system as a discrete-state, continuous time Markov process. Recently, an increasing number of works proposing non-Markovian methods is emerging, with the aim of providing more accurate representations of the random events observed experimentally. The need for non-Markovian modeling is also related to the finding of long-range memory and non-ergodicity.

In this special session we aim at collecting original research works reporting on topics related to the stochastic modelling of biological systems at different levels, ranging from the inter-molecular scale to the inter-cellular scale, including neural networks. Particular attention will be devoted to those proposals highlighting how the proposed modeling approach allows to gain insights on the investigated biological phenomenon and on the emerging properties of biological networks.

Dr. Paolo Paradisi
and Dr. Davide Chiarugi, Institute of Science and Technologies of Information (ISTI) - Italian National Research Council (CNR), Pisa (Italy)
SS19 Deep analysis of deep-sequencing data: for the discovery of genes, transcription factors, proteins and biomarkers

Deep-sequencing is emerging technology exhibits huge genomics and transcriptomics information about the livings. Extraction of critical genes is sometimes needs to further bioinformatics tools with functional evidences. In this session, we aimed to present recent developments and researches about the evaluation of the genomics and transcriptomics data in order to identify genes, gene families, transcription factors, biomarkers, SNPs, or etc. In this respect, we welcome to the studies exhibiting the analysis of RNA-seq data. In this session, the main topic covers the following researches:
  • Identification of genes, transcription factors, biomarkers, SNPs, SSRs, etc.
  • Bioinformatics tools in genome and transcriptome data-mining.
  • RNA-seq data analysis for the gene and protein discovery.
  • Modeling of cellular processes in livings.
Dr. Huseyin Tombuloglu
, Fatih University, Department of Biology, Istanbul (Turkey)

Dr. Guzin Kekec
, Fatih University, Vocational School of Medical Sciences, Istanbul (Turkey)