Virtual meeting link: https://meet.google.com/dgu-nqhw-xcf

Schedule details: https://drive.google.com/file/d/1LznF-Iji_GaY_DZKuHrprA0qEm28-YsB/view?usp=sharing

A biomarker (short for biological marker), is a measurable indicator of some biological state or condition. According to their functions, biomarkers can be categorized as drug-related biomarkers and disease-related biomarkers. Disease-related biomarkers can be further divided in three types: diagnostic biomarkers, which allow for the early detection of a disease in a noninvasive way; predictive biomarkers, which give an indication of the probable effect of a particular treatment on patients, and prognostic biomarkers, which show the progression of disease with or without treatment. Based on their properties, biomarkers can be classified as molecular biomarkers (e.g. genes, noncoding RNAs, lipids or metabolites), tissue biomarkers and digital (imaging) biomarkers.

Although plenty of biomarker-related data, such as expression data, interaction data, sequence data, and imaging data, have been collected and stored in various databases, devising efficient methods used to identify biomarkers remains a daunting task.

·         Advanced machine learning methods for molecular biomarker discovery from multi-modal data

·         Explainable deep learning for disease detection and prevention

·         Explainable intelligent systems for cancer screening, diagnosis including subtyping, prognosis, and treatment planning

·         Representation learning of biomarkers

·         Deep learning methods for digital biomarker discovery from medical Images

·         Deep learning for drug discovery, repositioning and repurposing

·         Deep learning for rational vaccine design

·         Deep learning for biomedical image analysis

·         Deep learning models for cellular communications

·         Deep learning models for single-cell transcriptomics

 Oct. 31, 2024: Due date for full workshop papers submission

 Nov.  14, 2024: Notification of paper acceptance to authors

 Nov.  21, 2024: Camera-ready of accepted papers

 Dec  3-6, 2024: Workshops

  FangXiang Wu, University of Saskatchewan, Canada

  Min Li, Central South University, China

  Luis Rueda, University of Windsor, Canada 

Bolin Chen, Northwestern Ploytechnical University, China

Xiujuan Lei, Shaanxi Normal University, China

Lingling Jin, University of Saskatchewan, Canada

Jiarui Ding, University of British Columbia, Canada

Alioune Ngom, University of Windsor, Canada

Yifeng Li, Brock University, Canada.

Mourad Elloumi, Université de Tunis, Tunis

Ignacio Rojas, University of Granada, Spain

Abed Alkhateeb, Princess Sumaya University for Technology, Jordan

Gonzalo Ruz, Universidad Adolfo Ibañez, Chile

Yan Yan, University of Guelph, Canada

Fei Wang, Anhui University, China

We accept two types of submission, through the online submission system (you can download the format instruction here (https://www.ieee.org/conferences/publishing/templates.html ). Electronic submissions in PDF format are required.

Full paper (6 - 8 pages IEEE 2-column format)

Short paper (2 - 4 pages IEEE 2-column format)

https://wi-lab.com/cyberchair/2024/bibm24/scripts/submit.php?subarea=S23&undisplay_detail =1&wh =/cyberchair/2024/bibm24/scripts/ws_submit.php

The selected authors of this workshop will be invited to submit their extensions to a special issue on  IET systems biology.