Interdisciplinary Project
A.Y. 2020/2021
Learning objectives
Hands-on experience in bioinformatics and genomics data processing using real world data and addressing real world scientific questions is essential for any future computational biologist. Likewise, a computational biologist needs to be able to interface between two rather different disciplines: computer science and (molecular) biology.
The participants will work in small teams on specific projects (ideally with members of both computational and biological backgrounds) and will regularly discuss the advancement of their work, including presentations about their preliminary results, open questions and future plans/tasks. Each project will be mentored by scientists working in the respective fields.
Apart from being able to present the own work in a clear manner, it is also important to correctly describe it. Therefore, a written report or short paper on the project and its results will be an essential requirement for the course.
The participants will work in small teams on specific projects (ideally with members of both computational and biological backgrounds) and will regularly discuss the advancement of their work, including presentations about their preliminary results, open questions and future plans/tasks. Each project will be mentored by scientists working in the respective fields.
Apart from being able to present the own work in a clear manner, it is also important to correctly describe it. Therefore, a written report or short paper on the project and its results will be an essential requirement for the course.
Expected learning outcomes
The objective of the course is to make students able to work on research projects that integrate both computational and biological aspects to address specific scientific problems, in a inter-disciplinary environment.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Lesson period
First semester
Course syllabus
Projects can be from widely different fields of computational biology and genomics, i.e., make use of different computational and statistical methods (including, for example, machine learning, network analysis, next generation sequencing data analysis), and regard quite different application domains (including, for example, cancer research, drug discovery, metagenomics).
There will be an initial meeting to discuss the different projects. Progress of a project will be evaluated through additional meetings with short presentations on the current state of the project and open questions. Participants are encouraged to give feedback to the individual presentations (e.g., style, clarity) and the project work (e.g., suggestions for improvement of alternative approaches).
The course will be concluded by full presentations of the projects and the obtained results, and the submission of the respective project reports or short papers.
There will be an initial meeting to discuss the different projects. Progress of a project will be evaluated through additional meetings with short presentations on the current state of the project and open questions. Participants are encouraged to give feedback to the individual presentations (e.g., style, clarity) and the project work (e.g., suggestions for improvement of alternative approaches).
The course will be concluded by full presentations of the projects and the obtained results, and the submission of the respective project reports or short papers.
Prerequisites for admission
Basic knowledge of programming and data processing, as well as basic knowledge in molecular biology.
Teaching methods
Seminars with project presentations by students followed by a scientific discussion and feedback session. Session with a brief introduction on report writing (structure, style, citations, etc.). Concluding "project conference" with full presentations.
Teaching Resources
As the individual projects require (or help to develop) widely differing biological knowledge and computational approaches, there is no "one fits all" reference material for this course. For the benefit of all participants, slides presented by the students during the course will be collected on the "Be e-Poli" (BeeP, the portal for the network activities of students and professors at the Politecnico di Milano, accessible from the Politecnico di Milano Web site; students registered to the course for the current academic year can access it.
Lists of project-specific reference material will likely be provided by the mentors of the individual projects.
Lists of project-specific reference material will likely be provided by the mentors of the individual projects.
Assessment methods and Criteria
The assessment is based on the final presentation (correctness, clarity, etc.) and the project report (correctness, clarity, etc.).
BIO/11 - MOLECULAR BIOLOGY
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
Lectures: 48 hours
Professor:
Piro Rosario Michael