In Silico Models to Validate Novel Blood-Based Biomarkers.

Sadlon, Angélique (2024). In Silico Models to Validate Novel Blood-Based Biomarkers. Methods in molecular biology, 2785, pp. 321-344. Springer 10.1007/978-1-0716-3774-6_20

Full text not available from this repository.

Biological validation of preliminary findings is a key prerequisite in biomarker discovery. In recent years, the development of advanced large-scale sequencing technologies combined with high-throughput computational analysis methods led to the extraction of considerable amount of data from healthy and diseased tissues. Stored in large open-access repositories, these data can be accessed and interrogated by researchers aiming at understanding the biological rationale behind their results. These so called in silico analyses, in opposite to in vitro analyses, have gained increasing importance in recent years, becoming a major component of research projects and publications. However, making sense of the large amount of data available can be challenging and may lead to a misinterpretation of the data. To reduce the dimensionality of this data, recent years have seen the development of statistical m\ethods and advanced graph analytics which help researchers summarize the available data and draw appropriate conclusions. In this chapter we will describe three in silico methods to investigate the biological underpinnings of a panel of seven blood-based biomarkers of Alzheimer's disease.

Item Type:	Journal Article (Original Article)
Division/Institute:	04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Institute of Clinical Chemistry
UniBE Contributor:	Sadlon, Angélique
Subjects:	600 Technology > 610 Medicine & health
ISSN:	1940-6029
Publisher:	Springer
Language:	English
Submitter:	Pubmed Import
Date Deposited:	04 Mar 2024 14:53
Last Modified:	04 Mar 2024 14:53
Publisher DOI:	10.1007/978-1-0716-3774-6_20
PubMed ID:	38427203
Uncontrolled Keywords:	Functional enrichment analysis Graph analytics In silico analysis Network analysis Omics
URI:	https://boris.unibe.ch/id/eprint/193699