Harmonizing semantic annotations for computational models in biology

Maxwell Lewis Neal; Matthias König; David Nickerson; Göksel Misirli; Reza Kalbasi; Andreas Dräger; Koray Atalag; Vijayalakshmi Chelliah; Michael T. Cooling; Daniel L. Cook; Sharon Crook; Miguel De Alba; Samuel H. Friedman; Alan Garny; John H. Gennari; Padraig Gleeson; Martin Golebiewski; Michael Hucka; Nick Juty; Chris Myers; Brett G. Olivier; Herbert M. Sauro; Martin Scharm; Jacky L. Snoep; Vasundra Touré; Anil Wipat; Olaf Wolkenhauer; Dagmar Waltemath

doi:10.1093/bib/bby087

Harmonizing semantic annotations for computational models in biology

Maxwell Lewis Neal^*
, Matthias König
, David Nickerson
, Göksel Misirli
, Reza Kalbasi
, Andreas Dräger
, Koray Atalag
, Vijayalakshmi Chelliah
, Michael T. Cooling
, Daniel L. Cook
, Sharon Crook
, Miguel De Alba
, Samuel H. Friedman
, Alan Garny
, John H. Gennari
, Padraig Gleeson
, Martin Golebiewski
, Michael Hucka
, Nick Juty
, Chris Myers

Brett G. Olivier, Herbert M. Sauro, Martin Scharm, Jacky L. Snoep, Vasundra Touré, Anil Wipat, Olaf Wolkenhauer, Dagmar Waltemath

^*Corresponding author for this work

AIMMS

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the COmputational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation.

Original language	English
Pages (from-to)	540-550
Number of pages	11
Journal	Briefings in bioinformatics
Volume	20
Issue number	2
DOIs	https://doi.org/10.1093/bib/bby087
Publication status	Published - 22 Mar 2019

Funding

This work was supported by the National Institutes of Health (grant number LM011969 to M.LN., D.L.C. and J.H.G.; GM109824 to M.L.N.; GM070923 to A.D., M.H. and N.L.; MH106674 and EB021711 to S.C.; GM123032 and EB023912 to H.M.S.); the German Federal Ministry of Education and Research (BMBF) (SEMS 031 6194 to D.W.; LiSyM 031L0054 to M.K.; LiSyM, 031L0056 to M.G.); the Aotearoa Foundation Fellowship (to D.N. and M.T.C.); the Medical Technologies Centre of Research Excellence (to R.K. and K.A.); the University of Auckland Faculty Research Development Fund (grant number 3714350 to R.K. and K.A.); the European Commission (grant number 731001 to M.de A.); the German Federal Ministry for Economic Affairs and Energy (NormSys 01FS14019 to M.G.); the Klaus Tschira Foundation (to M.G.); the United States of America’s National Science Foundation (grant numbers CCF-1748200, CCF-1218095, and DBI-1356041 to C.M.); the BE-Basic Foundation (grant number F08.005.001 to B.G.O.); the Department of Science and Technology/National Research Foundation in South Africa (grant number NRF-SARCHI-82813 to J.L.S.); the Biotechnology and Biological Sciences Research Council (grant numbers BBG0102181, BB/I004637/1 and BB/M013189/1 to J.L.S.) and Wellcome Trust (grant number 101445 to P.G.) in the UK; the Norwegian University of Science and Technology’s Strategic Research Area ‘NTNU Health’ (to V.T.); and ERACoSysMed (grant ID COLOSYS to V.T.); Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding agencies. This work was supported by the National Institutes of Health (grant number LM011969 to M.LN., D.L.C. and J.H.G.; GM109824 to M.L.N.; GM070923 to A.D., M.H. and N.L.; MH106674 and EB021711 to S.C.; GM123032 and EB023912 to H.M.S.); the German Federal Ministry of Education and Research (BMBF) (SEMS 031 6194 to D.W.; LiSyM 031L0054 to M.K.; LiSyM, 031L0056 to M.G.); the Aotearoa Foundation Fellowship (to D.N. and M.T.C.); the Medical Technologies Centre of Research Excellence (to R.K. and K.A.); the University of Auckland Faculty Research Development Fund (grant number 3714350 to R.K. and K.A.); the European Commission (grant number 731001 to M.de A.); the German Federal Ministry for Economic Affairs and Energy (NormSys 01FS14019 to M.G.); the Klaus Tschira Foundation (to M.G.); the United States of America's National Science Foundation (grant numbers CCF-1748200, CCF-1218095, and DBI-1356041 to C.M.); the BE-Basic Foundation (grant number F08.005.001 to B.G.O.); the Department of Science and Technology/National Research Foundation in South Africa (grant number NRF-SARCHI-82813 to J.L.S.); the Biotechnology and Biological Sciences Research Council (grant numbers BBG0102181, BB/I004637/1 and BB/M013189/1 to J.L.S.) and Wellcome Trust (grant number 101445 to P.G.) in the UK; the Norwegian University of Science and Technology's Strategic Research Area 'NTNU Health' (to V.T.); and ERACoSysMed (grant ID COLOSYS to V.T.);

Funders	Funder number
MedTech CoRE
Klaus Tschira Stiftung
Norges Teknisk-Naturvitenskapelige Universitet
Horizon 2020 Framework Programme
European Commission
Aotearoa Foundation
Bundesministerium für Wirtschaft und Energie	01FS14019
BE-Basic Foundation	F08.005.001
National Science Foundation	CCF-1748200, 1522074, 1218095, 1356041, 1748200, DBI-1356041, 731001
National Institutes of Health	MH106674, LM011969, EB021711, GM109824, GM123032, EB023912
Biotechnology and Biological Sciences Research Council	BB/I004637/1, BB/M013189/1, BBG0102181
Wellcome Trust	101445
Department of Science and Technology/National Research Foundation in South Africa	NRF-SARCHI-82813
National Institute of General Medical Sciences	R01GM070923
Bundesministerium für Bildung und Forschung	SEMS 031 6194, 031L0054, 031L0056
University of Auckland	3714350

Keywords

computational modeling
data integration
knowledge representation
modeling standards
semantic annotation

Access to Document

10.1093/bib/bby087

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6433895

Persistent URL (handle)

Persistent link

Cite this

Neal, M. L., König, M., Nickerson, D., Misirli, G., Kalbasi, R., Dräger, A., Atalag, K., Chelliah, V., Cooling, M. T., Cook, D. L., Crook, S., De Alba, M., Friedman, S. H., Garny, A., Gennari, J. H., Gleeson, P., Golebiewski, M., Hucka, M., Juty, N., ... Waltemath, D. (2019). Harmonizing semantic annotations for computational models in biology. Briefings in bioinformatics, 20(2), 540-550. https://doi.org/10.1093/bib/bby087

@article{bbb763a17903410081e220f84559c081,

title = "Harmonizing semantic annotations for computational models in biology",

abstract = "Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the COmputational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation.",

keywords = "computational modeling, data integration, knowledge representation, modeling standards, semantic annotation",

author = "Neal, \{Maxwell Lewis\} and Matthias K{\"o}nig and David Nickerson and G{\"o}ksel Misirli and Reza Kalbasi and Andreas Dr{\"a}ger and Koray Atalag and Vijayalakshmi Chelliah and Cooling, \{Michael T.\} and Cook, \{Daniel L.\} and Sharon Crook and \{De Alba\}, Miguel and Friedman, \{Samuel H.\} and Alan Garny and Gennari, \{John H.\} and Padraig Gleeson and Martin Golebiewski and Michael Hucka and Nick Juty and Chris Myers and Olivier, \{Brett G.\} and Sauro, \{Herbert M.\} and Martin Scharm and Snoep, \{Jacky L.\} and Vasundra Tour{\'e} and Anil Wipat and Olaf Wolkenhauer and Dagmar Waltemath",

year = "2019",

month = mar,

day = "22",

doi = "10.1093/bib/bby087",

language = "English",

volume = "20",

pages = "540--550",

journal = "Briefings in bioinformatics",

issn = "1467-5463",

publisher = "Oxford University Press",

number = "2",

}

Neal, ML, König, M, Nickerson, D, Misirli, G, Kalbasi, R, Dräger, A, Atalag, K, Chelliah, V, Cooling, MT, Cook, DL, Crook, S, De Alba, M, Friedman, SH, Garny, A, Gennari, JH, Gleeson, P, Golebiewski, M, Hucka, M, Juty, N, Myers, C, Olivier, BG, Sauro, HM, Scharm, M, Snoep, JL, Touré, V, Wipat, A, Wolkenhauer, O & Waltemath, D 2019, 'Harmonizing semantic annotations for computational models in biology', Briefings in bioinformatics, vol. 20, no. 2, pp. 540-550. https://doi.org/10.1093/bib/bby087

TY - JOUR

T1 - Harmonizing semantic annotations for computational models in biology

AU - Neal, Maxwell Lewis

AU - König, Matthias

AU - Nickerson, David

AU - Misirli, Göksel

AU - Kalbasi, Reza

AU - Dräger, Andreas

AU - Atalag, Koray

AU - Chelliah, Vijayalakshmi

AU - Cooling, Michael T.

AU - Cook, Daniel L.

AU - Crook, Sharon

AU - De Alba, Miguel

AU - Friedman, Samuel H.

AU - Garny, Alan

AU - Gennari, John H.

AU - Gleeson, Padraig

AU - Golebiewski, Martin

AU - Hucka, Michael

AU - Juty, Nick

AU - Myers, Chris

AU - Olivier, Brett G.

AU - Sauro, Herbert M.

AU - Scharm, Martin

AU - Snoep, Jacky L.

AU - Touré, Vasundra

AU - Wipat, Anil

AU - Wolkenhauer, Olaf

AU - Waltemath, Dagmar

PY - 2019/3/22

Y1 - 2019/3/22

N2 - Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the COmputational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation.

AB - Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the COmputational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation.

KW - computational modeling

KW - data integration

KW - knowledge representation

KW - modeling standards

KW - semantic annotation

UR - https://www.scopus.com/pages/publications/85063713612

UR - https://www.scopus.com/pages/publications/85063713612#tab=citedBy

U2 - 10.1093/bib/bby087

DO - 10.1093/bib/bby087

M3 - Article

C2 - 30462164

AN - SCOPUS:85063713612

SN - 1467-5463

VL - 20

SP - 540

EP - 550

JO - Briefings in bioinformatics

JF - Briefings in bioinformatics

IS - 2

ER -

Harmonizing semantic annotations for computational models in biology

Abstract

Funding

Keywords

Access to Document

Persistent URL (handle)

Other files and links

Fingerprint

Cite this