|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:
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):
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):
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).