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Doing research integrating concepts from physics&math with cell biology&immunology to promote in silico drug target&biomarker discovery
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Cso And Co-FounderCellazonUnited States -
Associate Director, Computational BiologyCell Signaling Technology (Cst) Feb 2023 - PresentDanvers, Ma, UsI lead a team of extremely capable scientists who aim to better understand and model cell signaling pathways and translate this knowledge into an efficient target discovery. Additionally, we develop new methods to discover antibodies against those targets, both empirically and in silico. Our target discovery efforts rely on the multimodal omics data (e.g., scRNAseq, proteomics) integration with the kinase-substrate specificity library, and further leveraging of such information to perform cell signaling pathway discovery both based on the pre-existing knowledge and de novo. To make these discoveries meaningful within the tissue context, my team effectively leverages multiplex spatial biology approaches. And actively contributes to this space with both multiplex assay and computational methods development. -
Principal Scientist, Lab HeadGenentech, Cancer Immunology Department (Systems Immunology) May 2019 - Nov 2022South San Francisco, California, UsAs part of Genentech's large scientific community, I led a research group of interdisciplinary scientists that aims to integrate concepts from physics/math with cell biology and immunology to promote in silico drug target and biomarker discovery in cancer immunology.Our research efforts contributed into two large subfields: digital pathology and systems immunology. We developed SPEX (Spatial Expression Explorer), a comprehensive image analysis pipeline thatwe implemented as a user-friendly web-based application with flexible plug-in analysis modules. These pipeline modules provide the end-to-end analysis by implementing a wide range of algorithms for cell segmentation, cell phenotyping, spatial expression patterns, cell-cell cooccurrence, and spatially informed pathway analysis. SPEX provides both infrastructure and quantitative analysis methods that allow for efficient store, manipulation and interactive visualization of spatial expression data. As part of system immunology efforts, we developed novel cell based assay and computational methods (biokinetic modeling, ML/AI) to quantitatively assess TCR-pMHC interaction specificity and kinetics. These research efforts open up the way to do in silico prediction of TCRs functional activity. -
Instructor (Non Tenure-Track Faculty)Stanford University Mar 2017 - May 2019Stanford, Ca, UsMy team was a part of a larger group headed by Dr. Leonore Herzenberg. I provided technical leadership to a small team of extremely capable software engineers and researchers in projects of computational immunology and statistics. Our research was broadly focused on mathematical modeling of cellular and molecular processes and development of statistical methods and software tools for computationally efficient and robust quantitative analysis of high-dimensional flow and mass cytometry data. -
Postdoctoral Fellow, Biophysics/ImmunologyStanford University Sep 2012 - Mar 2017Stanford, Ca, UsDeveloped cluster processing and ranking methods for analyzing high-dimensional flow and mass cytometry data.Developed dynamic flow cytometry method for quantification of cell-associated molecules without calibration. This technology removed a major barrier for estimating the number of expressed molecules on/in cells – a calibration procedure.
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Graduate Research Fellow, BiophysicsInstitute Of Biophysics Sep 2009 - Jul 2012Developed methodological approaches (quantitative flow cytometry, quantitative image cytometry) for study of antigen-antibody interactions in inhomogeneous media (both on the surface and inside cells).Quantitative studies of the higher-order chromatin dynamics.
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Graduate Research Fellow, PhysicsInstitute Of Chemical Kinetics And Combustion Sep 2006 - Nov 2011Developed scanning flow cytometry based methodologies to study neutrophil morphology and ligand-receptor interaction on human neutrophils. Developed biophysical model of human neutrophils and a method determining kinetic constants for neutrophil receptors that form the important pool of data relating to the initial stage of cell signaling.
Darya Orlova Skills
Darya Orlova Education Details
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Masaryk University BrnoBiophysics -
Institute Of Chemical Kinetics And Combustion, Novosibirsk, RussiaPhysics And Mathematics
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Novosibirsk State UniversityPhysics
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Novosibirsk State UniversityPhysics
Frequently Asked Questions about Darya Orlova
What company does Darya Orlova work for?
Darya Orlova works for Cellazon
What is Darya Orlova's role at the current company?
Darya Orlova's current role is CSO and Co-Founder.
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What schools did Darya Orlova attend?
Darya Orlova attended Masaryk University Brno, Institute Of Chemical Kinetics And Combustion, Novosibirsk, Russia, Novosibirsk State University, Novosibirsk State University.
What skills is Darya Orlova known for?
Darya Orlova has skills like Multi Color Flow Cytometry, Ligand Receptor Interactions, Mathematical Modeling, High Dimensional Data Analysis, Chemical Kinetics, Biokinetics, Ode, Cluster Analysis, Matlab, Scanning Flow Cytometry, Confocal Microscopy, Cell Culture.
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