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ICLS - Computational Life Sciences Day

In den Computational Life Sciences verbinden sich die Trends der Life Sciences und der Digitalisierung zu einem vielversprechenden Zukunftsfeld.

Computational Life Sciences Day 2022 - Perspectives

Die Tagung wird organisiert vom ICLS Institut für Computational Life Sciences.

Tagungsschwerpunkt

Mit der Etablierung des Instituts für Computational Life Sciences (entstanden aus dem Institut für Angewandte Simulation) und neuen Studienangeboten hat die ZHAW zukunftsweisende Zeichen gesetzt. Wir freuen uns daher, gemeinsam mit unseren Partnern aus der Forschung, Wirtschaft und Gesellschaft am 1. Computational Life Sciences Day unter dem Motto "Computational Life Sciences Perspectives" den Blick nach vorne zu richten. Wo stehen wir? Wo geht die Reise hin? Wo liegen die Potentiale?

Mit Freude laden wir Sie ein zu diesem Anlass des gegenseitigen Austauschs und Networkings ein. Neue Perspektiven entstehen, wenn sie gemeinsam geschaffen werden.

Programm

Zeit Agenda
09:00 - 09:30 Eröffnung und Begrüssung
Prof. Marcel Burkhard, Institutsleiter ICLS
09:30 - 10:15 Keynote
Delphine Scokaert, PhD, MBA
Business Product Manager - Lab insights - navify Algorithm Suite
Roche Diagnostics, Rotkreuz
10:15 - 10:45 Networking Break
10:45 - 11:00 Institute of Computational Life Sciences – Future Prospects
11:00 - 11:35 Gradually building up a digital twin of an automated production line
11:35 - 12:15 Digital Health Transforms Medical Care
12:15 - 13:30 Networking Lunch
13:30 - 13:35 Musikalisches Intro
13:35 - 13:50 Study programmes at ICLS
13:50 - 14:15 Pitches Master ACLS Students
14:15 - 14:45 Success Stories ACLS Alumni
14:45 - 15:15 Networking Break
15:15 - 15:50 PubMed Knowledge Graph; Leveraging Machine Learning, Natural Language Processing,
and Semantic Web for Literature-Based Discovery
15:55 - 16:30 Reinforcement Learning in Life Sciences
16:30 - 17:00 Schlusswort
Prof. Marcel Burkhard, Institutsleiter ICLS
17:00 Apéro Riche

Abstracts

Institute of Computational Life Sciences – Future Prospects

ICLS: Prof. Dr. Thomas Ott, Director of Institute ICLS from 01.01.2023
Abstract: The Institute of Computational Life Sciences at ZHAW is a player in a vibrant and exciting field. The four pillars (research centres) "Bioinformatics", "Cognitive Computing", "Digital Health", "Digital Labs and Production" form the basis for our current and future commitment to research and development at a high level and for the success of our study programmes. In this short presentation, I will venture an outlook on the opportunities and challenges we as an institute will face in the coming years together with our partners from science, business, and society. 

Gradually building up a digital twin of an automated production line

ICLS: Dr. Lukas Hollenstein, Co-Head of the Research Center Digital Labs & Production
Industry Partner: Daniel Fejzo, Engineering Project Lead, F. Hoffmann-La Roche Ltd Global Operations
Abstract: "Textbook examples" of Digital Twins, their interaction with the production line, often omit the early development stages with many uncertainties, many unanswered questions, and decisions to take. We discuss the process of building up a simulation model of an automated production line as a base for its development and iteration cycles as well as important lessons learned along the way.

Digital Health Transforms Medical Care

ICLS: Dr. Georg Spinner, Head of the Research Group Medical Image Analysis & Data Modeling
Industry Partner: TBA
Abstract: The digitalization of health care allows to gather and process data at unprecedented scale. Patient care and empowerment can be enhanced by quantitative methods in medicine. We will showcase how health data can be harvested and put to good use via the usage of patient-friendly wearable devices. 

Study programmes at ICLS

ICLS: Dr. Ivo Kaelin, Head of Studies
Abstract: From the autumn semester of 2022, the ICLS will not only be responsible for the Master's specialisation in Applied Computational Life Sciences (ACLS), but also for the new Bachelor's programme in Applied Digital Life Sciences (ADLS). The educational concept of this study programme is practice-oriented and offers a lot of freedom for the individual design of the curriculum. It focuses on three specialisations: "Digital Health", "Digital Labs and Production" and "Digital Environment" in close cooperation with industry.

Pitches Master ACLS Students

Speakers: Kevin Mohammad Yar, Leonie Grossmann, Adrian Rutzer
Abstract: In short "Flash Talks", current Master's students from the ACLS programme present the projects they are working on as part of their Master's thesis, in collaboration with research groups at the ZHAW or in industry.

Success Stories ACLS Alumni

Speakers: Lukas Schaub (Peleven AG), Anna Wróbel (ZHAW / UZH)
Abstract: Graduates of the ACLS Master's programme present the areas in which they are working today, as well as their experiences and perspectives.

PubMed Knowledge Graph; Leveraging Machine Learning, Natural Language Processing, and Semantic Web for Literature-Based Discovery

ICLS: Dr. Ahmad Aghaebrahimian, Research Associate, Research Center Bioinformatics
Industry Partner: TBA
Abstract: The rapid expansion of publication production in the life sciences makes it a challenge for researchers to keep up with new findings and studies across the globe. PubMed alone houses more than 34 million articles from over 5000 journals. These articles contain billions of explicit facts such as "Raynaud's syndrome->associated with->platelet aggregability" or "Dietary fish oil->reduces->platelet aggregability". Yet, these facts are scattered across disjoined articles making it hard to infer the resulting implicit hypothesis "Dietary fish oil->?->Raynaud's syndrome". Literature-based discovery (LBD) aims at generating implicit hypotheses via associating seemingly unrelated facts from the graph of disjoint publications. Aiming at facilitating automatic LBD, we do R&D on the latest advances in Deep Learning, Natural Language Processing, and Semantic Web technologies for populating a Knowledge Graph given the entire PubMed.

Reinforcement Learning in Life Sciences

ICLS: Session Chair: Dr. Claus Horn, Head of the Research Group Autonomous Systems and Reinforcement Learning
Industry Partner: Fruitful Farming AG, Kikodo Education Technologies Sàrl
Abstract: Life Sciences are full of temporal processes with huge optimization potential, for which the emerging field of applied Reinforcement Learning – the third learning paradigm of Machine Learning -  offers a powerful new approach. We will showcase this approach with some use cases from our current research activity.