Computational challenges of personalized medicine
One of the most highly anticipated promises of Precision or Personalized Medicine (PM) is to offer improved treatment by taking into account the unique genetic, phenotypic, population and environmental profile of the individual. As of today we have experienced a tremendous progress towards this. From a computational perspective, this progress lies in areas like management of big data from molecular and genome profiling technologies, availability of public and open databases for mutations and diseases, and development of highly tested computations methods for data analysis. Moreover we have experienced an increase in electronic health record data management environments that put forward issues like privacy and security without sacrificing interoperability and usability.
On the road towards making PM a reality, there are still many issues that remain largely unsolved. For example, modern methods and data are still inadequate to untangle the biological mechanisms that regulate the development of some of the common, and most of the rare diseases. This is partly due to limitations of modern profiling technologies, but it is also due to shortcomings in bioinformatics and computational biology. Another factor that hinders progress is that science still remains isolated due to lack of environments for data integration and reluctancy for scientific collaboration. A last eminent issue is the lack of consensus on guidelines and practices for genetic data interpretation than can help clinicians make the right decision and deliver the optimal treatment.
In this workshop we welcome submissions that bring forward these issues and suggest tangible solutions. Specifically this workshop covers the following areas:
- Environments for data and tool standardization, integration and harmonization
- Techniques for Genetic / Medical / Population data collection, access and sharing
- FAIR policies and methods that promote scientific collaboration
- Analysis of existing regulations for medical data privacy and security
- Collaboration and Compliance with large European infrastructures and initiatives
- Implementation of population-specific characteristics in genomic analyses of diseases
- Computational methods for identification of phenotype-genotype associations from multivariate or high-dimensional data
- Guidelines for genomic data interpretation in modern healthcare environments
|Paper Submission Deadline||August 5, 2019|
|Paper Notification||August 20, 2019|
|Paper Camera-Ready Paper Submission||August 30, 2019|
Tentative Program Committee