• 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 Expanding Concept of Chaperone Therapy for Inherited Brain Diseases

Chaperone therapy is a new concept of molecular therapeutic approach, first developed for lysosomal diseases, utilizing small molecular competitive inhibitors of lysosomal enzymes. This concept has been gradually targeted to many diseases of other categories, utilizing various compounds not necessarily competitive inhibitors but also non-competitive inhibitors or endogenous protein chaperones (heat-shock proteins).

In this session we will discuss current trends of chaperone therapy targeting various types of neurological and non-neurological diseases caused by misfolded mutant proteins. This molecular approach will open a new therapeutic view for wide variety of diseases, genetic and non-genetic, and neurological and non-neurological, in the near future.

Yoshiyuki Suzuki, M.D., Ph.D.
, Tokyo Metropolitan Institute of Medical Science (Japan).

SS2 Quantitative and Systems Pharmacology: Thinking in a wider "systems-level" context accelerates drug discovery and enlightens our understanding of drug action

"Quantitative and Systems Pharmacology (QSP) is an emerging discipline focused on identifying and validating drug targets, understanding existing therapeutics and discovering new ones. The goal of QSP is to understand, in a precise, predictive manner, how drugs modulate cellular networks in space and time and how they impact human pathophysiology." (QSP White Paper - October, 2011)

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 current post-genomic era, the aim is to design drugs that perturb biological networks rather than individual targets. The challenge is to be able to consider the complexity of physiological responses to treatments at very early stages of the drug development. In this way, current effort has been put into combining 0 chemogenomics with network biology to implement new network-pharmacology approaches to drug discovery; i.e. polypharmacology approaches combined with systems biology information, which advance further in both improving efficacy and predicting unwanted off-target effects. Furthermore, the use of network biology to understand drug action outputs treasured information, i.e for pharmaceutical companies, such as alternative therapeutic indications for approved drugs, associations between proteins and drug side effects, drug-drug interactions, or pathways and gene associations which provide leads for new drug targets that may drive drug development.

Following the line of QSP Workshops I and II (2008, 2010), the QSP White Paper (2011), or QSP Pittsburgh Workshop (2013), the goal of this symposium is to bring together interdisciplinary experts to help advance the understanding of how drugs act, with regard to their beneficial and toxic effects, by sharing new integrative, systems-based computational or experimental approaches/tools/ideas which allow to increase the probability that the newly discovered drugs will prove therapeutically beneficial, together with a reduction in the risk of serious adverse events.

Violeta I. Perez-Nueno, Ph.D.
, Senior Scientist, Harmonic Pharma, Nancy (France).

SS3 Hidden Markov Model (HMM) for Biological Sequence Modeling

Sequence Modeling is one of the most important problems in bioinformatics. In the sequential data modeling, Hidden Markov Models(HMMs) have been widely used to find similarity between sequences. 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;

Mohammad Soruri
, Department of Electrical and Computer Engineering, University of Birjand, Birjand (Iran).

SS4 Advances in Computational Intelligence for Bioinformatics and Biomedicine

Biomedicine and, particularly, Bioinformatics are increasingly and rapidly becoming data-based sciences, an evolution driven by technological advances in image and signal non-invasive data acquisition (exemplified by the 2014 Nobel Prize in Chemistry for the development of super-resolved fluorescence microscopy). In the Biomedical field, the large amount of data generated from a wide range of devices and patients is creating challenging scenarios for researchers, related to storing, processing and even just transferring information in its electronic form, all these compounded by privacy and anonymity legal issues. This can equally be extended to Bioinformatics, with the burgeoning of the .omics sciences.

New data requirements require new approaches to data analysis, some of the most interesting ones are currently stemming from the fields of Computational Intelligence (CI) and Machine Learning (ML). This session is particularly interested in the proposal of novel CI and ML approaches to problems in the biomedical and bioinformatics domains.

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

  • Novel applications of existing CI and ML methods to biomedicine and bioinformatics.
  • Novel CI and ML techniques for biomedicine and bioinformatics.
  • CI and ML based methods to improve model interpretability in biomedical problems, including data/model visualization techniques.
  • Novel CI and ML techniques for dealing with non.structured and heterogeneous data formats.

More information at


Main Organizer:
Alfredo Vellido, PhD
, Department of Computer Science, Universitat Politécnica de Catalunya, BarcelonaTECH (UPC), Barcelona (Spain).

Jesus Giraldo, PhD, Institut de Neurociències and Unitat de Bioestadística, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Barcelona (Spain).
René Alquézar, PhD, Department of Computer Science, Universitat Politecnica de Catalunya, BarcelonaTECH (UPC), Barcelona (Spain).
SS5 Tools for Next Generation Sequencing data analysis

Next Generation Sequencing (NGS) is the main term used to describe a number of different modern sequencing technologies such as Illumina, Roche 454 Sequencing, Ion torrent, SOLiD sequencing and Pacific Biosciences. These technologies allow us to sequence DNA and RNA more quickly and cheaply than Sanger sequencing and have opened new ways for the study of genomics, transcriptomics and molecular biology, among others.

The continuous improvements on those technologies (longer read length, better read quality, greater throughput, etc) and the broad application of NGS in several research fields, have produced (and still produce) a huge amount of software tools for the analysis of NGS genomic/transcriptomic data.

We invite authors to submit original research, pipelines and review articles on topics related to software tools for NGS data analysis such as (but not limited to):

  • Tools for data pre-processing (quality control and filtering).
  • Tools for sequence alignment.
  • Tools for de novo assembly.
  • Tools for the analysis of genomic data: identification and annotation of genomic variants (variant calling, variant annotation).
  • Tools for functional annotation to describe domains, orthologues, genomic variants, controlled vocabulary (GO, KEGG, InterPro...).
  • Tools for the analysis of transcriptomic data: RNA-Seq data (quantification, normalization, filtering, differential expression) and transcripts and isoforms finding.
  • Tools for Chip-Seq data.
  • Tools for "big-data" analysis of reads and assembled reads.

Javier Perez Florido, PhD
, Genomics and Bioinformatics Platform of Andalusia (GBPA), Seville, (Spain).
Antonio Rueda Martin, Genomics and Bioinformatics Platform of Andalusia (GBPA), Seville, (Spain).
M. Gonzalo Claros Diaz, PhD, Department of Molecular Biology and Biochemistry, University of Malaga (Spain).
SS6 Dynamics networks in system medicine

Over the past two decades, it is increasingly recognized that a biological function can only rarely be attributed to an individual molecule. Instead, most biological functions arise from signaling and regulatory pathways connecting many constituents, such as proteins, and small molecules, allowing them to adapt to environmental changes. "Following on from this principle, a disease phenotype is rarely a consequence of an abnormality in a single effector gene product, but reflects various processes that interact in a complex network". Offering a unifying language to describe relations within such a complex system has made network science a central component of systems biology and recently system medicine. Despite the knowledge that biological networks can change with time and environment, much of the efforts have taken a static view. Time-varying networks support richer dynamics and may better reflect underlying biological changes in abnormal state versus normal state and this provides a powerful motivation and application domain for computational modelling. We introduce this session on the Dynamics Networks in System Medicine to encourage and support the development of computational methods that elucidate the dynamic network and its application in medicine. We will discuss current trends and potential biological and clinical applications of network-based approaches to human disease. We aim to bring together experts in different fields in order to promote cross fertilization between different communities.

Narsis Aftab Kiani, PhD
, Computational Medicine Unit, Department of Medicine, Karolinska Institute (Sweden).
SS7 Interdisciplinary puzzles of measurements in biological systems

Natural sciences demand measurements of the subject of interest as a necessary part of the experimental process. Thus, for the proper understanding of the obtained datasets, it is the necessity to take into the question all mathematical, biological, chemical or technical conditions affecting the process of the measurement itself. While assumptions and recommendations within the field itself are usually concerned, some issues, especially discretization, quantization, experiment time, self-organization and consequent anomalous statistics might cause puzzling behavior.

In this special section we will describe particular examples across disciplines with joint systems theory based approach, including noise and baseline filtration in mass spectrometry, image processing and analysis, and distributed knowledge database. The aim of this section is to present an general overview of the systemic approach.

Jan Urban, PhD
, Laboratory of Signal and Image Processing, Institute of Complex Systems, Faculty of Fisheries and protection of Waters, University of South Bohemia.(Czech republic).
SS8 Biological Networks: Insight from interactions

Post genomic era has ushered to say 'Ome' for integrated biology disciplines. The complete sequencing of the human genome has shown us a new era of Systems Biology (SB) referred to as omics'. From genomics to proteomics and furthermore, 'Omics'-es existing nowadays integrate many areas of biology. This resulted in an essential ascent from Bioinformatics to Systems Biology leaving room for identifying number of interactions in a cell. Tools have been developed to utilize evolutionary relationships towards understanding uncharacterized proteins while there is a need to generate and understand functional interaction networks. A systematic understanding of genes and proteins in a regulatory network has resulted in bringing the birth of System Biology (SB), there by raising several questions unanswered. Through this conference, we will dig some questions on why and how interactions especially protein-protein interactions (PPI) are useful while discussing methods to remove false positives by validating the data. The conference is aimed at the following two focal themes:

  • Bioinformatics and systems biology for deciphering the known unknown regions.
  • Systems Biology of regulatory networks and machine learning.

Prof. Alfredo Benso, PhD
, Department of Control and Computer Engineering, Politecnico di Torino (Italy)
Dr. Prashanth Suravajhala, PhD, Founder of Bioclues.org and Director of Bioinformatics.org
SS9 Tissue engineering for biomedical and pharmacological applications

The concept of tissues appeared more than 200 years ago, since textures and attendant differences were described within the whole organism components. Instrumental developments in optics and biochemistry subsequently paved the way to transition from classical to molecular histology in order to decipher the molecular contexts associated with physiological or pathological development or function of a tissue. The aim of this special session is to provide an overview of the most cutting edge updates in tissues engineering technologies. This will cover the most recent developments for tissue proteomics, and the applications of the ultimate molecular histology method in pathology and pharmacology: MALDI Mass Spectrometry Imaging. This session will be of great relevance for people willing to have a relevant summary of possibilities in the field of tissue molecular engineering.

Rémi Longuespée, PhD
, Laboratoire de Spectrométrie de Masse, University of Liege (Belgium).