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MLGED 2018 - Advances in Machine Learning Techniques Applied to Gene Expre...

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Special Session

Advances in Machine Learning Techniques Applied to Gene Expression Data - MLGED 2018

19 - 21 January, 2018 - Funchal, Madeira, Portugal

Within the 9th International Conference on Bioinformatics Models, Methods and Algorithms - BIOINFORMATICS 2018


SCOPE


Gene expression is a measurement of expression levels of various genes at once, with the intent to discover his function. One way to analyze this expression data is through clustering techniques, which aim to group genes of similar expression tendencies together. The current big problem in this research area is the huge amount of data that needs to be processed simultaneously, which require the development of new techniques and algorithms, principally on machine learning advances. This special session aims to show recent advances in the area, presenting new techniques of processing, automated analysis and pattern classification. It also intends to be a forum for sharing experiences between specialists, researchers and beginners in the area, presenting and discussing relevant ideas.

TOPICS:
- Clustering algorithms;
- Biclustering algorithms;
- Automated gene expression analysis;
- Deep learning applied to genetic data;
- New machine learning techniques.


IMPORTANT DATES

Paper Submission: November 7, 2017 (expired)
Authors Notification: November 21, 2017
Camera Ready and Registration: November 29, 2017


SPECIAL SESSION PROGRAM COMMITTEE

Jessica Carballido, Universidad Nacional del Sur, Argentina
Miguel Rocha, University of Minho, Portugal
Priscila Saito, Universidade Tecnológica Federal do Paraná, Brazil


CHAIR

Paulo Eduardo Ambrosio
Universidade Estadual de Santa Cruz
Brazil

Brief Bio

Doctor in Medical Sciences. Research interest: Computational Biology, Pattern Recognition.



SCOPE

The purpose of the International Conference on Bioinformatics Models, Methods and Algorithms is to bring together researchers and practitioners interested in the application of computational systems, algorithmic concepts and information technologies to address challenging problems in Biomedical research with a particular focus on the emerging problems in Bioinformatics and computational biology. There is a tremendous need to explore how mathematical, statistical and computational models can be used to better understand biological processes and systems, while developing new methodologies and tools to analysis the massive currently-available biological data. Areas of interest to this community include systems biology, sequence analysis, biostatistics, image analysis, network and graph models, scientific data management and data mining, machine learning, pattern recognition, computational evolutionary biology, computational genomics and proteomics, and related areas.

BIOINFORMATICS encourages authors to submit papers to one of the main topics indicated below, describing original work, including methods, techniques, advanced prototypes, applications, systems, tools or survey papers, reporting research results and/or indicating future directions. Accepted papers will be presented at the conference by one of the authors and published in the proceedings. Acceptance will be based on quality, relevance and originality. There will be both oral and poster sessions.
The proceedings will be indexed by several major international indexers.
Special sessions are also welcome. Please contact the secretariat for further information on how to propose a special session.



CONFERENCE TOPICS


  • Simulation and Modeling
  • Computational Intelligence
  • Genomics and Proteomics
  • Sequence Analysis
  • Structural Bioinformatics
  • Structure Prediction
  • Structural Variations
  • Image Analysis
  • Visualization
  • Databases and Data Management
  • Data mining and Machine Learning
  • Biostatistics and Stochastic Models
  • Pharmaceutical Applications
  • Systems Biology
  • Algorithms and Software Tools
  • Web Services in Bioinformatics
  • Computational Molecular Systems
  • Immuno- and Chemo-informatics
  • Pattern Recognition, Clustering and Classification
  • Model Design and Evaluation
  • Transcriptomics
  • Next Generation Sequencing



BIOSTEC KEYNOTE SPEAKERS

Anatole Lécuyer, Inria Rennes/IRISA, Hybrid Research Team, France
Corina Sas, Lancaster University, United Kingdom
Dinesh Kumar, RMIT University, Australia
Maximiliano Romero, Università Iuav di Venezia, Italy


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Date and Time

Location

Vila Galé Santa Cruz

Rua São Fernando, 5

RNET 1012

9100-173 Santa Cruz

Portugal

View Map

Refund Policy

No Refunds

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