Topics covered during the conference include (but are not limited to):

 

 

 

In addition to the traditional panels, this year the Call includes the following Special Sessions proposed by members of the Society:

 

A detailed description of the Special Sessions is available at the end of this Call.

 

Contributions will be accepted for both traditional and special sessions and should address novel bioinformatics methods, algorithms, databases, tools and applications for research and development.

 

Abstracts will be reviewed by the Scientific Committee and accepted for oral communication and poster presentation or rejected in case they do not match the scientific standards of the conference. Two or three anonymous referees will evaluate each abstract. We encourage the authors to use the maximum space available in the submission form in order to describe at the best their work and results.

 

Accepted abstracts will be collected in the conference proceedings.

 

Negotiations are ongoing for the publication of a Supplement of BMC Bioinformatics (or other international journals) with full articles dedicated to the subjects presented at the conference as poster or oral communications.

 

Abstract submission requires early registration to the conference of the presenting author after the acceptance notification.

 

Important dates:

 

November 15, 2013: Opening of the Call for Abstracts

December 20, 2013: Deadline for Abstract submission for oral communications and posters

January 20, 2014: Abstract acceptance notification (Oral communications and posters)

January 24, 2014: Deadline for early registration to the conference (required for authors of accepted abstracts)

February 26–28, 2014: BITS2013 meeting

 

 

 

Abstract submission form will be available soon. Please visit the BITS web site at www.bioinformatics.it for updates and links to meeting web site and submission form.

 

Special Sessions

 

In addition to the traditional panels, this year the Call includes the following Special Sessions proposed by members of the Society:

 

 

 

 

The introduction of NGS technologies pushed the completion of many novel genomes, as well as the resequencing of genomes from related genotypes. Moroever, the low economical and experimental efforts today required for deeper molecular investigations on the functionalities of the genomes further increase the challenges for Bioinformatics, to make sense of the available data, to manage “omics” resources, to provide ease of access to the users.

Being in the HOT omics era, strong and innovative Bioinformatics is needed.

The session aims to highlight successful efforts and still present issues in facing the challenge.

 

 

'Big data' management, storage and analysis is one of the most pressing issues in Biomedical Science, Clinical Bioinformatics and Biobanking. Data set size can grow up to levels where traditional storage methods (relational databases, flat files, etc.) are insufficient. Next-generation sequencing data require novel paradigms for metadata management and file-tracking on top of the requirement for adequate storage and computational units. Nowadays, scientific studies in the fields are evolving towards global scale collaborations at a multi-disciplinary levels, involving scientists located in different geographical regions. Data collection and processing require an extensive use of metadata, to improve information sharing and availability. As the geographical distribution of the involved partners grows from local to global scales, a unique metadata standardization is not feasible, and metadata must be designed in a flexible and dynamic way, yet providing a minimal structure. Moreover, it is increasingly important to integrate data coming from different disciplines, such as patient clinical history/record, biological/genomic data, and structural/functional images (tomographies, histological images, etc...). Innovative data management approaches are indispensable to focus on research tasks without the burden of gathering the relevant information among scattered datasets. Various solutions involve, among others, highly flexible and extensible data/metadata models, advanced and distributed storage solutions (data Grids, digital libraries, etc...), and, possibly, semantic/ontology integration. This session aims at evaluating the state of the art, recent approaches, open challenges, and the potential future developments of data management in Biomedical Science.

 

 

 

Recently there has been a significant interest in the stochastic approach for modelling biochemical systems, mainly because experimental data are providing evidences that the stochasticity arising at the molecular level plays important roles in determining the overall behaviour of 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 of biochemical systems are proving to be useful tools for gaining insights about the role played by stochastic events in determining the global dynamics of biochemical networks.

These approaches represent an alternative to traditional continuous deterministic modelling, especially when the systems in hand are composed by a small number of elements as, e.g., single living cells. In these cases random fluctuations must be properly taken into account and deterministic descriptions provided by the so-called Reaction Rate Equations fail both in predicting the fluctuations in molecule populations 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 biochemical reactions consist in describing the temporal evolution of the considered system as a discrete-state, continuos 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.

In this special session we aim at collecting original research works reporting on topics related to the Markovian and non-Markovian modelling of biochemical systems. Particular attention will be devoted to those proposal highlighting how the used computational method allows to gain insights on the mechanisms underlying the modelled phenomena.

 

 

 

 

 

Synthetic Biology is a fast growing research field, aimed at engineering existent cells or de novo synthesizing artificial cells. In doing this, theoretical models and computational tools are needed to explore and screen among possible experimental realizations. A tight link is therefore established with Bioinformatics and Systems Biology. In particular, this session will focus bottom-up synthetic cells, a wet-lab model that paves the way to studies in different and relevant areas, from the origin of life to the targeted drug delivery. Theoretical and computational models are here of critical importance, since the design of a consistent and effective synthetic cell, able to perform some biological action, is performed by means of good theoretical models and powerful computational tools. This session is open to researchers working on synthetic biology from an experimental and/or theoretical point of view, they are encouraged to present new Bioinformatics/Systems Biology challenges raised by Synthetic Biology approaches.