Knowledge-based translational medicine is a rapidly growing discipline in biomedical research and aims to expedite the discovery of new diagnostic tools and treatments by using a multi-disciplinary, highly collaborative, "bench-to-bedside" approach. Large amounts of multi-omics, imaging (medical and molecular) and clinical data can now be captured for given patient populations. In addition to the challenges of data curation and harmonisation, new computational methods are required to identify molecular signatures that suggest disease subtype. These signatures may be predictive of outcome or progression, and impact on disease management by suggesting personalised therapeutic strategies for patients. Such approaches will further the development of a new taxonomy of disease.
In the TransMed COSI meeting, we will explore the current status of computational biology approaches within the field of translational medicine.
Information of previous TransMed meeting(s) can be found here.
Link to the ISMB 2020 website is:here
- The meeting will be in the form of online meeting.
- Proceedings Submission Deadline: Monday, January 30, 2020. Detail information.
- The TransMed COSI meeting will take place on July 15th, 2020, during the ISMB 2020 Virtual event.
Topics of interest
Topics of interest include, but are not limited to:
- Clinical and molecular data storage and integration infrastructure, including: data warehousing for translational medicine, multi-‘omics and clinical data integration, data visualization in translational medicine
- Curation and harmonization of clinical, ‘omics and imaging data, including: standards and ontologies in translational medicine, biomedical text mining and semantic representation
- Data analytics for patient stratification, biomarker and target discovery, including: disease subtype discovery, Electronic Health Records integration, translational imaging, multi-scale modelling, high performance and cloud computing in translational medicine, mathematical modelling for disease processes, pathways and networks
- Computational approaches for target selection and drug discovery, including: druggability assessment and target selection, polypharmacology, drug reuse, chemical library design, virtual screening technologies, drug discovery enabler pipelines and databases, chemical tool analysis.
- ADME/PK and Tox models, including: databases and modeling approaches for ADME and PK, machine learning approaches to predicting toxicity, modeling of pharmacokinetics to man and model organism utility models.
- Translational Medicine Informatics Applications/Case Studies, including: Next generation sequencing annotation and biomedicine applications, clinical data integration and application.
Jason H. Moore, Edward Rose, M.D. and Elizabeth Kirk Rose, M.D. Professor, University of Pennsylvania, United States
Keynote title: 20 Challenges of AI in Medicine
Abstract: The opportunities for using artificial intelligence (AI) and machine learning to improve healthcare are endless. Recent successes include the use of deep learning to identify clinically important patterns in radiographic images. However, there are numerous important challenges which must be addressed before AI can become widely adopted and incorporated into clinical workflows. Some of these challenges come from healthcare data. For example, clinical data from electronic health records (EHR) are notoriously noisy and incomplete. Some of these challenges come from the limitations of AI algorithms. For example, each algorithm looks at data in a different manner. How do you know which are the right methods to employ for a given data set? We will review 10 important clinical data challenges and 10 AI challenges which can impede progress in this area. A number of specific examples and some possible solutions will be provided.
Atul Butte, Priscilla Chan and Mark Zuckerberg Distinguished Professor of Pediatrics, Bioengineering & Therapeutic Sciences, and Epidemiology & Biostatistics at UCSF, United States
Keynote title: TBD
Time zone: EDT
|Start time||End time||Topic|
|10:40 AM||11:20 AM||Keynote (Live-stream) - 20 Challenges of AI in Medicine - Jason H. Moore|
|11:20 AM||11:40 AM||Proceedings (Pre-recorded with live Q&A)- Privacy-preserving Construction of Generalized Linear Mixed Model for Biomedical Computation - Rui Zhu|
|12:00 PM||12:20 PM||(Pre-recorded with live Q&A) - Longitudinal multi-omics profiling reveals two biological seasonal patterns in California - Ahmed Metwally|
|12:20 PM||12:30 PM||(Pre-recorded with live Q&A) - A versatile non-linear transfer learning framework for correcting pre-clinical-based predictors of drug response - Soufiane Mourragui|
|12:30 PM||12:40 PM||Q&A|
|2:00 PM||2:20 PM||Proceedings (Pre-recorded with live Q&A) - Robust and accurate deconvolution of tumor populations uncovers evolutionary mechanisms of breast cancer metastasis - Yifeng Tao|
|2:20 PM||2:30 PM||(Pre-recorded with live Q&A) - Deep Hidden Physics Modeling of Cell Signaling Networks - Rune Linding|
|2:30 PM||2:40 PM||(Pre-recorded with live Q&A) - A deep transfer learning model for extending in vitro CRISPR-Cas9 viability screens to tumors - Yu-Chiao Chiu|
|2:40 PM||2:50 PM||(Pre-recorded with live Q&A) - The evolution of homologous repair deficiency in high grade serous ovarian carcinoma - Colin Semple|
|2:50 PM||3:00 PM||Q&A|
|3:20 PM||3:40 PM||Proceedings (Pre-recorded with live Q&A) - Identifying diagnosis-specific genotype-phenotype associations via joint multi-task sparse canonical correlation analysis and classification - Lei Du|
|3:40 PM||4:00 PM||(Pre-recorded with live Q&A) - POCOVID-Net: Automatic Detection of COVID-19 From a New Lung Ultrasound Imaging Dataset (POCUS) - Jannis Born|
|4:00 PM||4:20 PM||(Pre-recorded with live Q&A) - Drug repurposing to improve health and lifespan in humans - Handan Melike Donertas|
|4:20 PM||4:30 PM||(Pre-recorded with live Q&A) - Patient Derived Xenografts Based Pharmacogenomics for Precision Medicine - Arvind Singh Mer|
|4:30 PM||4:40 PM||Q&A|
|5:00 PM||5:10 PM||(Pre-recorded with live Q&A) - ReactomeGSA - Efficient Multi-Omics Comparative Pathway Analysis - Johannes Griss|
|5:10 PM||5:50 PM||Keynote (Live-stream) - Precisely Practicing Medicine from 700 Trillion Points of Data - Atul Butte|
|5:50 PM||6:00 PM||Closing remarks (Live-stream) Maria Secrier|
Authors are invited to submit abstracts (1 page) for presentations and posters by April 2, 2020. Acceptance notification will be sent out by April 30, 2020.
For proceedings submission the deadline is Monday, January 30, 2020
Please use the EasyChair submission system.
- Detail information can be found: here.
Due to current COVID19 situation, this year ISMB 2020 is going virtual!
Please follow the registration page on the ISMB website: TransMed COSI Registration.
Venkata Satagopam, Luxembourg Centre For Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg
Reinhard Schneider, Luxembourg Centre For Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg
Maria Secrier, University College London, UK
Wei Gu, Luxembourg Centre For Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg
Mansoor Saqi, King’s College London, UK
Programme committee (alphabetical order)
TBD, TBD, TBD
If you have any questions, please do not hesitate to contact us: firstname.lastname@example.org.
Google Groups: TransMed2020 Google Group
The current TransMed logo was designed by Belinda Hanson.
The previous TransMed logo was designed by Alexandre Pellet, www.alexandrepellet.com.