Author Archives: Andreas Scherer

Andreas Scherer

About Andreas Scherer

Andreas Scherer, Ph.D has managed global software and services businesses working for publicly traded companies such as Netscape and AOL as well as privately held companies. As part of his academic work, he has developed algorithms to conduct DNA sequence analysis. In the last decade, he has focused on accelerating R&D processes of Fortune 500 pharmaceutical, biotech, and medical device companies. As a result of this work, he is intimately familiar with the domestic and international life sciences market. Dr. Scherer holds a PhD in Computer Science from the University of Hagen, Germany, and a Master of Computer Science from the University of Dortmund, Germany. He is author and co- author of over 20 international publications and has written books on project management, the Internet, and artificial intelligence. His latest book, “Be Fast Or Be Gone,” is a prizewinner in the 2012 Eric Hoffer Book Awards competition and has been named a finalist in the 2012 Next Generation Indie Book Awards. Follow Andreas on Twitter @andreasscherer or connect with him on LinkedIn.

  

New eBook Release: Clinical Variant Analysis for Cancer

Applying AMP Guidelines to Analyze Somatic Variants Today, I am thrilled to share with you the launch of a brand new eBook titled “Clinical Variant Analysis for Cancer – Applying AMP Guidelines to Analyze Somatic Variants”. We would happy to send you a complimentary copy which can be requested on our website here. The clinical utilization of Next-Gen Sequencing data… Read more »

Genetic Testing for Cancer – New Version Release

Yesterday, I released a new version of my eBook, “Genetic Testing for Cancer – Third Edition”. We would be happy to send you one! To download a complimentary copy, please submit a request on our site here. In 1914, the German cytologist Theodor Boveri coined the phrase “Cancer is a disease of the genome.” At this time, his ideas were… Read more »

Clinical Variant Analysis: Part V

Examples of Clinical Variant Interpretation with VSClinical In this chapter, I’d like to go through a few examples for variants that have been classified with the help of VSClinical. This will give you a better understanding of how data sources are actually being represented in the software and how those are used to make decisions on applicable criteria. It goes… Read more »

Clinical Variant Analysis: Part IV

Rules for Combining Various Classification Criteria Now that we have a solid understanding of how the various criteria are meant to be applied, it’s time to look at how the evidence collectively leads to the clinical categorization of a variant. Let’s go through the rule framework for combining the various criteria. Pathogenic In order for a variant to be classified… Read more »

Clinical Variant Analysis: Part III

Clinical Variant Analysis – Classification Criteria of Benign Variants The classification of benign variants is overall simpler and more straightforward, with the majority of benign variants being eliminated through allele frequency in various population catalogs. BA1 If a variant is common in one or more population catalog, as indicated by the allele frequency associated by the appropriate sub-population, it can… Read more »