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Inference of Genome-Scale Gene Regulatory Networks: Are There Differences in Biological and Clinical Validations?

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Predictive Medicine and Data Analytics Lab, Department of Signal Processing, Tampere University of Technology, 33720 Tampere, Finland
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Institute of Biosciences and Medical Technology, 33520 Tampere, Finland
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Department of Mechatronics and Biomedical Computer Science, University for Health Sciences, Medical Informatics and Technology (UMIT), 6060 Hall in Tyrol, Austria
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College of Computer and Control Engineering, Nankai University, Tianjin 300071, China
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Institute for Intelligent Production, Faculty for Management, University of Applied Sciences Upper Austria, Steyr Campus, 4400 Steyr, Austria
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Author to whom correspondence should be addressed.
Mach. Learn. Knowl. Extr. 2019, 1(1), 138-148; https://doi.org/10.3390/make1010008
Received: 27 July 2018 / Revised: 17 August 2018 / Accepted: 20 August 2018 / Published: 22 August 2018
(This article belongs to the Section Network)
Causal networks, e.g., gene regulatory networks (GRNs) inferred from gene expression data, contain a wealth of information but are defying simple, straightforward and low-budget experimental validations. In this paper, we elaborate on this problem and discuss distinctions between biological and clinical validations. As a result, validation differences for GRNs reflect known differences between basic biological and clinical research questions making the validations context specific. Hence, the meaning of biologically and clinically meaningful GRNs can be very different. For a concerted approach to a problem of this size, we suggest the establishment of the HUMAN GENE REGULATORY NETWORK PROJECT which provides the information required for biological and clinical validations alike. View Full-Text
Keywords: machine learning; network inference; genomics; network science; experimental validation; biomarker; causal networks; applied statistics machine learning; network inference; genomics; network science; experimental validation; biomarker; causal networks; applied statistics
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Emmert-Streib, F.; Dehmer, M. Inference of Genome-Scale Gene Regulatory Networks: Are There Differences in Biological and Clinical Validations? Mach. Learn. Knowl. Extr. 2019, 1, 138-148.

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