Training for translation between disciplines: A philosophy for life and data sciences curricula

K. Anton Feenstra, Sanne Abeln, Johan A. Westerhuis, Filipe Brancos Dos Santos, Douwe Molenaar, Bas Teusink, Huub C.J. Hoefsloot, Jaap Heringa

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Motivation: Our society has become data-rich to the extent that research in many areas has become impossible without computational approaches. Educational programmes seem to be lagging behind this development. At the same time, there is a growing need not only for strong data science skills, but foremost for the ability to both translate between tools and methods on the one hand, and application and problems on the other. Results: Here we present our experiences with shaping and running a masters? programme in bioinformatics and systems biology in Amsterdam. From this, we have developed a comprehensive philosophy on how translation in training may be achieved in a dynamic and multidisciplinary research area, which is described here. We furthermore describe two requirements that enable translation, which we have found to be crucial: sufficient depth and focus on multidisciplinary topic areas, coupled with a balanced breadth from adjacent disciplines. Finally, we present concrete suggestions on how this may be implemented in practice, which may be relevant for the effectiveness of life science and data science curricula in general, and of particular interest to those who are in the process of setting up such curricula.

Original languageEnglish
Pages (from-to)i4-i12
Number of pages9
JournalBioinformatics
Volume34
Issue number13
Early online date27 Jun 2018
DOIs
Publication statusPublished - 1 Jul 2018

Cite this

@article{b68d2763ae894f62bd2d2e7f4838a9f7,
title = "Training for translation between disciplines: A philosophy for life and data sciences curricula",
abstract = "Motivation: Our society has become data-rich to the extent that research in many areas has become impossible without computational approaches. Educational programmes seem to be lagging behind this development. At the same time, there is a growing need not only for strong data science skills, but foremost for the ability to both translate between tools and methods on the one hand, and application and problems on the other. Results: Here we present our experiences with shaping and running a masters? programme in bioinformatics and systems biology in Amsterdam. From this, we have developed a comprehensive philosophy on how translation in training may be achieved in a dynamic and multidisciplinary research area, which is described here. We furthermore describe two requirements that enable translation, which we have found to be crucial: sufficient depth and focus on multidisciplinary topic areas, coupled with a balanced breadth from adjacent disciplines. Finally, we present concrete suggestions on how this may be implemented in practice, which may be relevant for the effectiveness of life science and data science curricula in general, and of particular interest to those who are in the process of setting up such curricula.",
author = "{Anton Feenstra}, K. and Sanne Abeln and Westerhuis, {Johan A.} and {Brancos Dos Santos}, Filipe and Douwe Molenaar and Bas Teusink and Hoefsloot, {Huub C.J.} and Jaap Heringa",
year = "2018",
month = "7",
day = "1",
doi = "10.1093/bioinformatics/bty233",
language = "English",
volume = "34",
pages = "i4--i12",
journal = "Bioinformatics",
issn = "1367-4803",
publisher = "Oxford University Press",
number = "13",

}

Training for translation between disciplines : A philosophy for life and data sciences curricula. / Anton Feenstra, K.; Abeln, Sanne; Westerhuis, Johan A.; Brancos Dos Santos, Filipe; Molenaar, Douwe; Teusink, Bas; Hoefsloot, Huub C.J.; Heringa, Jaap.

In: Bioinformatics, Vol. 34, No. 13, 01.07.2018, p. i4-i12.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - Training for translation between disciplines

T2 - A philosophy for life and data sciences curricula

AU - Anton Feenstra, K.

AU - Abeln, Sanne

AU - Westerhuis, Johan A.

AU - Brancos Dos Santos, Filipe

AU - Molenaar, Douwe

AU - Teusink, Bas

AU - Hoefsloot, Huub C.J.

AU - Heringa, Jaap

PY - 2018/7/1

Y1 - 2018/7/1

N2 - Motivation: Our society has become data-rich to the extent that research in many areas has become impossible without computational approaches. Educational programmes seem to be lagging behind this development. At the same time, there is a growing need not only for strong data science skills, but foremost for the ability to both translate between tools and methods on the one hand, and application and problems on the other. Results: Here we present our experiences with shaping and running a masters? programme in bioinformatics and systems biology in Amsterdam. From this, we have developed a comprehensive philosophy on how translation in training may be achieved in a dynamic and multidisciplinary research area, which is described here. We furthermore describe two requirements that enable translation, which we have found to be crucial: sufficient depth and focus on multidisciplinary topic areas, coupled with a balanced breadth from adjacent disciplines. Finally, we present concrete suggestions on how this may be implemented in practice, which may be relevant for the effectiveness of life science and data science curricula in general, and of particular interest to those who are in the process of setting up such curricula.

AB - Motivation: Our society has become data-rich to the extent that research in many areas has become impossible without computational approaches. Educational programmes seem to be lagging behind this development. At the same time, there is a growing need not only for strong data science skills, but foremost for the ability to both translate between tools and methods on the one hand, and application and problems on the other. Results: Here we present our experiences with shaping and running a masters? programme in bioinformatics and systems biology in Amsterdam. From this, we have developed a comprehensive philosophy on how translation in training may be achieved in a dynamic and multidisciplinary research area, which is described here. We furthermore describe two requirements that enable translation, which we have found to be crucial: sufficient depth and focus on multidisciplinary topic areas, coupled with a balanced breadth from adjacent disciplines. Finally, we present concrete suggestions on how this may be implemented in practice, which may be relevant for the effectiveness of life science and data science curricula in general, and of particular interest to those who are in the process of setting up such curricula.

UR - http://www.scopus.com/inward/record.url?scp=85050803847&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85050803847&partnerID=8YFLogxK

U2 - 10.1093/bioinformatics/bty233

DO - 10.1093/bioinformatics/bty233

M3 - Article

VL - 34

SP - i4-i12

JO - Bioinformatics

JF - Bioinformatics

SN - 1367-4803

IS - 13

ER -