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Mark D'Ascenzo is listed as Research Scientist @ UW Medicine | Data Science, Bioinformatics at UW Medicine, a company with 2300 employees, based in Seattle, Washington, United States. AeroLeads shows a matched LinkedIn profile for Mark D'Ascenzo.
Mark D'Ascenzo previously worked as Research Scientist at Uw Medicine and Consultant at Precyte Inc. Mark D'Ascenzo holds Ms, Biomedical Engineering from Cornell University.
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As a Data Scientist with a background in biomedical engineering, I specialize in developing and evaluating machine learning (ML) classifiers for disease prediction. With a strong programming background, I have expertise in leveraging Python and R for data analytics and modeling projects. Additionally, I have extensive experience in bioinformatics, specifically in analyzing large-scale genomic and transcriptomic data, as well as computational biology, including the application gene expression and network analysis for biomarker discovery. I am passionate about leveraging data-driven approaches to derive meaningful insights and make a positive impact in the field of biomedical research.
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Seattle, Washington, United States
As part of a translational research team within the Department of Neurological Surgery, I'm contributing to multiomic-based research efforts to further the groups initiative in brain cancer research and treatment.
Seattle, Washington, United States
As part of an NIH SBIR funded research project, I collaborated with a team at Seattle Children's Research Institute (SCRI) to contribute to a translational effort to advance PreCyte's blood-based diagnostic assay, iCAP. Initially developed at the Institute for Systems Biology (ISB), this assay uses cells as biosensors to monitor gene expression changes in.
Greater Seattle Area
My primary focus in this role was to investigate the diagnostic potential of the iCAP assay for early detection of Alzheimer's disease (AD). Using cells as biosensors, I employed RNA-Seq and network-based approaches to study gene expression changes in iPSC-derived neurons, aiming to identify potential biomarkers capable of discriminating between pre-MCI.
Seattle, Washington, United States
Expertise in: - Machine Learning - Statistical Analyses - Genomic Analysis (NGS) - Gene Expression Analysis - Data Visualization - Python and R - Scalable Analytics
Waltham, Massachusetts, United States
AlloVir is a gene therapy startup (Series B) focused on developing viral therapies for patients having a weakened immune system. I am exploring relationships between primary and secondary endpoints in Phase 3 clinical trial data, distilling complex trends from an extensive clinical trial database. Following AlloVir's strategic decision to discontinue their.
Greater Seattle Area
Working closely with clinical research scientists, I utilized machine learning techniques to evaluate and improve the accuracy of somatic variant calls in NGS data obtained from FFPE samples. In a separate project, I took the lead in a collaborative effort with the Engineering team, where we developed a custom visualization tool for analyzing time-series.
In close collaboration with the wet-lab and Engineering teams, I contributed to early research and development (R&D) initiatives, focusing on the enhancement of capture uniformity for SeqCap EZ target enrichment products, including whole exome and panel designs. I developed algorithms to quantify and improve coverage over challenging genomic regions.
Machine learning. Proteomics. Protein expression analysis of CSF in Alzheimer’s disease. Application of LDA and Random Forest models to.
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Mark D'Ascenzo works for UW Medicine.
Mark D'Ascenzo is listed as Research Scientist @ UW Medicine | Data Science, Bioinformatics at UW Medicine.
Mark D'Ascenzo is based in Seattle, Washington, United States while working with UW Medicine.
Mark D'Ascenzo has worked for Uw Medicine, Precyte Inc, Data Science / Bioinformatics / Computational Biology, Allovir, and Roche.
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Mark D'Ascenzo holds Ms, Biomedical Engineering from Cornell University.
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