Taking Open Innovation to the Molecular Level ‐ Strengths and Limitations

Zdrazil, Barbara; Blomberg, Niklas; Ecker, Gerhard F.

doi:10.1002/minf.201200014

Cited by 8 publications

(4 citation statements)

References 33 publications

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“…In the knowledge areas of Medicine, Molecular Medicine, Pharmacology and Chemoinformatics, the positive impact of open data and open innovation on drug discovery and development processes is analysed [77,79]. Lastly, in Museology, the impetus of open data and open innovation in museums, libraries and archives is discussed [63].…”

Section: Studied Themes By Knowledge Areamentioning

confidence: 99%

Open Data for Open Innovation: An Analysis of Literature Characteristics

Corrales-Garay¹,

Mora-Valentín²,

Ortiz‐de‐Urbina‐Criado³

2019

Future Internet

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In this paper, we review some characteristics of the literature that studies the uses and applications of open data for open innovation. Three research questions are proposed about both topics: (1) What journals, conferences and authors have published papers about the use of open data for open innovation? (2) What knowledge areas have been analysed in research on open data for open innovation? and (3) What are the methodological characteristics of the papers on open data for open innovation? To answer the first question, we use a descriptive analysis to identify the relevant journals and authors. To address the second question, we identify the knowledge areas of the studies about open data for open innovation. Finally, we analyse the methodological characteristics of the literature (type of study, analytical techniques, sources of information and geographical area). Our results show that the applications of open data for open innovation are interesting but their multidisciplinary nature makes the context complex and diverse, opening up many future avenues for research. To develop a future research agenda, we propose a theoretical model and some research questions to analyse the open data impact process for open innovation.

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Section: Studied Themes By Knowledge Areamentioning

confidence: 99%

Open Data for Open Innovation: An Analysis of Literature Characteristics

Corrales-Garay¹,

Mora-Valentín²,

Ortiz‐de‐Urbina‐Criado³

2019

Future Internet

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“…Moreover, biological activity measures are derived from functionally different assays, performed in different cell lines. This makes it difficult to compile all data available into one large set and might lead to a drastic reduction of the size of final training set 41. Thus, the provenance of the data will be of vital importance for utilizing the full power of open data.…”

Section: Discussionmentioning

confidence: 99%

How Far Could We Go with Open Data – A Case Study for TRPV1 Antagonists

Tsareva

Ecker

2013

Molecular Informatics

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Publicly open databases of small compounds have become an indispensable tool for chemoinformaticians for collection and preparation of datasets suitable for drug discovery questions. Since these databases comprise compounds coming from structure-activity relationship (SAR) studies performed by different research groups, they are very diverse with respect to the biological assays used. In the present study we analyzed the applicability of a thoroughly curated dataset gathered from open sources for ligand-based studies, using the transient receptor potential vanilloid type 1 (TRPV1) as use case. Thorough curation of compounds according to the biological assay type and conditions led to a dataset of comparable bioactive chemicals. Subsequent exhaustive analysis of the obtained dataset using classification algorithms demonstrated that the models obtained in most of the cases possess reliable quality. Analysis of constantly misclassified compounds showed that they belong to local SAR series, where small changes in structure lead to different class labels. These small structural differences could not be captured by the classification algorithms. However application of the 3D alignment-independent QSAR technique GRIND for local, structurally related series overcomes this problem.

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“…Some of these have a very broad scope and are government-funded like the European Innovative Medicines Initiative (IMI) [41], which includes multiple programs like the Joint European Compound Library [42] and Open PHACTS [43], others are more focused like the Structural Genomics Consortium (http://www. thesgc.org/) [44], or geared toward specific diseases [45].…”

Section: Consortiamentioning

confidence: 99%