Call for Papers

The massive parallel sequencing technologies (e.g., Next Generation Sequencing) for DNA- and RNA- sequencing (DNA-seq and RNA-seq) produced a large amount of data that needed to be processed, stored and shared by also taking into account its own integrity and privacy.

The traditional relational database management systems (RDBMS) have some limitations in terms of effectiveness and efficiency on large matrix data, typically encountered in genomic research. Otherwise, a NoSQL database offers several advantages to relational models. It, as well as the methodologies applied on this one for querying, overcome the limitations of relational databases, by also offering advantages in terms of scalability. However, NoSQL databases are often immature and lack standards, e.g., regarding the query language.

Bioinformatics allows data processing and analysis from heterogeneous sources, e.g., in order to model Interaction Networks from multi-omics data, to investigate genome-wide genetic markers to predict the breeding value of selection candidates, or to extract knowledge from biological and clinical data.

The Workshop focuses the attention on a wide range of data-based (or data-centered) bioinformatics topics and applications, related to genetics, molecular and systems biology, including reviews of software tools and methods. Its main goal is to bring together scientists in the fields of bioinformatics, databases, data science, and medical informatics, as well as scientists working in application-related fields (e.g., biology and medicine), to discuss the challenges and the requirements related to high-throughput data processing and knowledge mining in bioinformatics. Furthermore, the use of novel technologies, architectures and models to develop novel high-performance and parallel algorithms will be discussed.

The workshop will consider articles describing novel computational algorithms and software tools, data models, databases, as well as novel methodologies based on artificial intelligence and systems biology. Papers must focus on original research contributions related to scientific knowledge currently published in literature, and/or formal assessments of software tools and methods for data persistence, genomic selection, and knowledge extraction, in bioinformatics.

List of Topics

Topics of interest include (but are not limited to):

●   Data models for omics data 

●   Intelligent mining of large-scale biomedical data

●   Network analysis

●   Artificial intelligence and machine learning for data-based bioinformatics

●   Massive parallel computation of biomedical and clinical data

●   Non-conventional architectures (e.g., GPUs, FPGAs) in bioinformatics for data querying or processing

●   NoSQL (Distributed / Big Data) Databases in bioinformatics

●   Data dimension reduction methods in high-dimensional space (e.g., embeddings) databases

●   Cloud computing (e.g., serverless) in bioinformatics

●   Pattern recognition techniques

●   High Performance Computing in bioinformatics

●   Software tools and databases

●   Text mining and bioinformatics

●   Bioinformatics research and applications

Additional Information

Contact: Pietro Cinaglia, Magna Graecia University, Italy.