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Dan Vanatta is a computational biochemist who received his Ph.D. in Chemistry from Stanford University in 2015. His dissertation focused on simulations of antibiotic resistance in bacteria. During graduate school, he developed novel algorithms to interpret computational models based on experimental data and statistically analyzed the activation pathways of bacterial signaling protein NtrC. He has published papers on the origin of molecular resistance to vancomycin and the network of molecular switches that control NtrC activation. Currently, he is a postdoctoral researcher at Stanford University studying phosphorylation and protein activation through molecular dynamics simulations and statistical analysis.
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This document provides a summary of Jennifer Shelton's background and experience in bioinformatics. It outlines her education in biology and post-baccalaureate studies. Her research focuses on de novo genome and transcriptome assembly using next-generation sequencing and BioNano Genomics data. She has extensive experience developing bioinformatics workflows and teaching coding skills through workshops. Currently she is the Bioinformatics Core Outreach Coordinator at Kansas State University where she continues her research and outreach efforts.
Joseph Granger one page resume times new roman
Joseph B. Granger has extensive education and experience in biochemistry. He received his M.S. in Biochemistry from Dartmouth College where he developed nanoparticles to inhibit ACAT1 in the CNS. As a Ph.D. candidate at Dartmouth, he produced peptide-tagged liposomes and micelles to deliver therapeutics to treat Alzheimer's disease models. He has proficiency in various laboratory techniques and software programs. Granger has experience teaching biochemistry and conducting undergraduate research investigating the structure-function relationship of a bacterial regulator protein.
Resume Prahlad Rao 06042011
Prahlad Rao has over 5 years of experience conducting proteomics research to understand protein regulation in mycobacterial cells and their interactions with macrophages. He has a Ph.D. in pharmaceutical biotechnology from the University of Illinois and experience working in proteomics facilities analyzing various sample types. Rao has published several papers analyzing protein turnover and networks in mycobacterial cells under different stresses using mass spectrometry techniques.
Molecular docking.pptx
Molecular docking is a computational technique used in drug discovery to predict how small molecules, like potential drug candidates, bind to protein targets. It involves exploring different orientations of a ligand when bound to the target protein's binding site to form a stable complex. The results of molecular docking help researchers identify ligands that strongly and specifically interact with proteins, guiding drug development and optimization efforts. Key components of molecular docking include the 3D structures of the target protein and ligand, as well as a grid that defines the protein's binding site for efficient sampling of ligand poses. Popular molecular docking software includes AutoDock, DOCK, Glide, and SwissDock.
Macromolecular interaction
The document discusses electrostatic interactions and methods for predicting protein-nucleic acid interactions. It covers the role of electrostatics in determining biomolecular structure and interactions. It also describes Poisson-Boltzmann theory as a framework for modeling electrostatics and various software tools that solve the Poisson-Boltzmann equation. Finally, it outlines different approaches for modeling and predicting protein-nucleic acid interactions, including molecular dynamics simulations and statistical and knowledge-based potential functions.
20170128_Resume_Engineering
Aaron Tan is a post-doctoral research fellow at the University of Michigan who received his Ph.D. in Materials Science and Engineering from the University of Michigan in 2012. His research focuses on using atomic force microscopy techniques to study the properties and dynamics of thin polymer films and biological materials. He has authored several publications in materials characterization and developed new methods for measuring electrical, thermal, and mechanical properties at the nanoscale.
MOLECULAR DOCKING.pptx
A swift introduction to the history of computer aided drug design, concept of molecular docking, its theory, its applications in biomedical researches and its pressing limitations.
Mpp Rsv 2008 Public
The Molecular Programming Project (MPP) is a collaboration between Caltech and University of Washington aimed at developing the theory and practice of programming molecular systems. The goals of the MPP are to: 1) create programming languages and compilers for molecular programming; 2) develop a theoretical framework for analyzing and designing molecular programs; 3) experimentally validate their compilers and theory with larger molecular programs than currently possible; 4) apply their technologies to real-world applications; and 5) train a new generation of molecular programmers.
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DanVanattaCV
- 1. DanVanattaComputational Biochemist education 2009–2015 Ph.D., Chemistry Stanford University Dissertation: Simulations of Antibiotic Resistance in Bacteria 2005–2009 B.S. Honors, Chemistry University of California, Berkeley research 2009–2015 Graduate Researcher Stanford University Advisor: Vijay Pande • Generated and analyzed large scale datasets with molecular dynamics and Markov Models on distributed computing network Folding@Home. • Developed novel algorithms and work flows to interpret computational models based on experimental data. • Statistically evaluated the activation pathways of conformational change in key bacterial signaling protein (NtrC) to discover stabilizing molecular interactions. • Recapitulated experimental binding trend for vancomycin with cell wall precursor and applied statistical analysis to calculate error bars. • Tested and improved in-house analysis pipelines (MSMBuilder and Fold- ing@Home) 2008–2009 Undergraduate Researcher UC Berkeley Advisor: Phillip Geissler Created C++ program to model self-assembly of nano rods for use in solar panels 2007-2008 Undergraduate Researcher UC Berkeley Advisor: Richard Andersen Synthesized and analyzed bonding of air-sensitive transition metal - ligands publications 2015 Dan Vanatta, Vijay Pande. Origin of Molecular Resistance to Vancomycin. In Submission to JCTC. 2015 Dan Vanatta, Diwakar Shukla, Morgan Lawrenz, Vijay Pande. A Network of Molecular Switches Control the Activation of the Two-Component Response Regulator NtrC. Nat. Commun. 6:7283 doi: 10.1038/ncomms8283 (2015) 2015 Diwakar Shukla, Dan Vanatta, Vijay Pande. Activation of Kinases by Phosphory- lation. In preparation contact 1 (408) 242-7611 Clark Center S296 318 Campus Dr. Stanford, CA 94305 dan.vanatta@gmail.com github.com/dvanatta linkedin.com/in/dvanatta1 programming Python(numpy, matplotlib) Bash, C++, Ruby R, Matlab, SQL, VMD Gromacs & MSMBuilder databases Uniprot/Swissprot PharmGKB Entrez interests Rock Climbing, Basketball, Guitar, Mountain Biking
- 2. teaching 2009–2010 Teaching Assistant Stanford University Organic Chemistry Lecture & Lab 2007-2008 Undergraduate Student Instructor UC Berkeley ChemScholars & General Chemistry 2007-2009 Willard Youth Support Program Willard Middle School, Berkeley, CA Volunteer Math Tutor & Mentor academic projects 2013 Researched pharmacogenomic potential of the interaction between metoprolol and Cytochrome P450. 2012 Wrote Python code to: • Perform global ends-free and local alignment using Needleman-Wunsch dynamic programming algorithm with affine gap penalty • Classify gene expression microarray experiments using K-nearest neigh- bor supervised machine learning algorithm. • Cluster genes with similar expression profiles using K-means unsuper- vised machine learning algorithm. • Build a network of protein connections using a cheminformatic approach to compare proteins by examining the similarity of ligands they bind. invited presentations 2013 Molecular-Switches Control the Activation of NtrC CMAD Seminar, Stanford, CA 2012 Predicting Conformational Change in NtrC Student Seminar, Stanford, CA 2010 New Directions in Predictions of Protein Allostery A.S.P. retreat, Las Vegas, NV posters 2013 Molecular-Switches Control the Activation of NtrC BPS 2014, SF, CA 2012 Understanding Protein Conformational Change CUP XII, Santa Fe, NM awards 2014-2015 Simbios Fellowship Stanford University 2010-2014 Stanford Center for Molecular Analysis and Design Fellowship Stanford University 2012-2013 Hong Kong Graduate Fellowship Stanford University 2007 Bruce Howard Memorial Scholarship UC Berkeley