posted by user: alessio_ferone || 7256 views || tracked by 7 users: [display]

CIMB 2020 : EAIS2020 Special Session on Computational Intelligence methods in bioinformatics

FacebookTwitterLinkedInGoogle

 
When May 27, 2020 - May 29, 2020
Where Bari, Italy
Submission Deadline Feb 8, 2020
Notification Due Mar 6, 2020
Final Version Due Mar 20, 2020
Categories    bioinformatics   data mining   machine learning   fuzzy
 

Call For Papers

Aims and scope:
In modern biomedical research, high‐throughput technologies, such as the next generation sequencing, produces huge data sets. High‐throughput data are collected in the broad context of genomics, epigenomics, transcriptomics and proteomics. From these data, it is possible to explain the pathogenesis or predict the predisposition and/or the clinical outcome of several human diseases, among which psychiatric, cardiovascular, obesity, aetiology of a number of diseases such as cancer, schizophrenia, and Alzheimer, just to name a few.
The key factor to exploit such rapid growth of biological data is to develop strategies that would allow the analysis at the rate at which it’s gathered. Moreover, in many real‐life circumstances, a timely response or prediction could be vital for saving lifes. In this context, the identification of new strategies for processing and analyzing such kind of data is becoming more and more necessary since their large amount of data can sometimes represent a real obstacle to effectively identify the most relevant patterns and to build comprehensive models capable of explaining complex biological phenotypes.
The aim of the special session is to host original papers and reviews on recent research advances and the state‐of‐the‐art methods in the fields of Computational Intelligence, Machine Learning Data Mining and Distributed Computing methodologies concerning with the processing of omics data in order to shed light about the relationship between genotype and disease‐related phenotype.
Relevant topics within this context include, but are not limited to:
- Machine learning
- Sparse Coding
- Data Mining
- Fuzzy and Neuro‐Fuzzy Systems
- Probabilistic and statistical modelling
- OMICs in the context of genomics, epigenomics, transcriptomics anroteomics
- Evaluation of protein folding and/or protein‐ligand interactions (where ligands are proteins, DNA, RNA and small molecules), also in the context of genetic variation
- Identification of potential gene regulatory elements (i.e., binding oranscription factors, miRNAs, etc.)
- Analysis of common genetic variants (i.e., SNPs, HLA genotypesicrosatellites)
- Analysis of experimental data from next‐generation sequencing
- Analysis of gene expression data
- Biomedical applications
Paper Submission Guidelines
Papers should be submitted through EasyChair (https://easychair.org/conferences/?conf=ieeeeais2020) by “Computational Intelligence methods in Bioinformatics” in the Special Sessions section. See conference web site (www.eais2020.di.uniba.it) for detailed formatting instructions.
Important Dates
Paper Submission Deadline: January 10, 2020 Decision Notification: February 19, 2020 Final Paper Submission: March 20, 2020

Related Resources

IJCAI 2022   31st International Joint Conference on Artificial Intelligence
CVPR 2022   Computer Vision and Pattern Recognition
IEEE WCCI 2022   IEEE World Congress on Computational Intelligence
JCRAI 2021-Ei Compendex & Scopus 2021   2021 International Joint Conference on Robotics and Artificial Intelligence (JCRAI 2021)
IEEE--ICCIA--EI, Scopus 2022   IEEE--2022 7th International Conference on Computational Intelligence and Applications (ICCIA 2022)--EI Compendex, Scopus
MLDM 2022   18th International Conference on Machine Learning and Data Mining
PRA 2022   2022 4th Workshop on Pattern Recognition Applications (PRA 2022)
CMCA 2022   11th International Conference on Control, Modelling, Computing and Applications
ICCIA--IEEE, Ei, Scopus 2022   IEEE--2022 7th International Conference on Computational Intelligence and Applications (ICCIA 2022)--EI Compendex, Scopus
DASFAA 2022   Database Systems for Advanced Applications