posted by user: program1011 || 1735 views || tracked by 3 users: [display]

CMMM 2020 : Special Issue on Machine Learning Applications in Single-Cell RNA Sequencing Data

FacebookTwitterLinkedInGoogle

Link: https://www.hindawi.com/journals/cmmm/si/810784/
 
When N/A
Where N/A
Submission Deadline Apr 23, 2021
Categories    machine learning   deep learning   bioinformatics
 

Call For Papers

The invention of single-cell RNA sequencing (scRNA-seq) has led to the generation of tremendous amounts of data pertaining to populations of cells of specific interest. However, one of the major challenges associated with analysing such data includes designing efficient machine learning approaches that can cope with the noise and sparsity existing in data.

Examples of machine learning applications for scRNA-seq data include: identifying biomarkers of dementia and Alzheimer’s disease; identifying candidate drugs for numerous other neurological disorders; identifying putative cell types from scRNA-seq data of various diseases; noise filtering of low quality cells; pseudo-time reconstruction; and proposals of new clustering methods for scRNA-seq. The success behind machine learning applications depends on the development of new machine learning techniques.

This Special Issue invites not only machine learning researchers, but also researchers interested in potential applications to scRNA-seq data. Both research and review articles pertaining to new machine learning methods and applications to the interpretation of scRNA-seq data are welcomed.

Potential topics include but are not limited to the following:

Supervised learning
Unsupervised learning
Semi-supervised learning
Active learning
Transfer and multitask learning
Ranking
Deep learning
Representation learning
Parallel and distributed learning approaches
Distance learning
Ensemble methods
Dimensionality reduction methods

Lead Editor
* Turki Turki, Department of Computer Science, King Abdulaziz University, Jeddah, Saudi Arabia. Contact Email: tturki@kau.edu.sa

Guest Editors
* Y-h. Taguchi, Department of Physics, Chuo University, Tokyo, Japan. Contact Email: tag@granular.com
* Sanjiban Sekhar Roy, School of Computer Science and Engineering, Vellore Institute of Technology, India, Contact Email: sanjibanroy09@gmail.com

Related Resources

ICDM 2021   21th Industrial Conference on Data Mining
IARCE 2021-Ei Compendex & Scopus 2021   2021 5th International Conference on Industrial Automation, Robotics and Control Engineering (IARCE 2021)
MLDM 2021   17th International Conference on Machine Learning and Data Mining
22nd EANN 2021   22nd Engineering Applications of Neural Networks
17th AIAI (IFIP WG 12.5) 2021   Artificial Intelligence Applications and Innovations
CiVEJ 2020   Civil Engineering and Urban Planning: An International Journal
SI-DAMLE 2020   Special Issue on Data Analytics and Machine Learning in Education
ML_BDA 2021   Special Issue on Machine Learning Technologies for Big Data Analytics
Signal 2021   8th International Conference on Signal and Image Processing
Fintech 2020   Sustainaility (Q2): Fintech: Recent Advancements in Modern Techniques, Methods and Real-World Solutions