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Biography: Dr. Anita Bandrowski: Dr. Bandrowski works at the Center of research in biological systems at UCSD on the RRID Initiative and SciCrunch. The goal of Dr. Bandrowski's work is to improve research reproducibility by making sure that key biological resources such as antibodies are identifiable in the scientific literature.
Anita works at UCSD on the Neuroscience Information Framework, she is also the Founder and CEO of SciCrunch which provides services for RRIDs
Dr. Maryann Martone: I am a neuroanatomist by training, but for the past decade I have been working in the area of neuroinformatics to increase access to and utilization of neuroscience data. I recently completed my tenure as President of FORCE11, the Future of Research Communications and e-Scholarship, a non-profit organization dedicated to transforming scholarly communication. I was instrumental in coordinating the working group that issued the Joint Declaration of Data Citation and FAIR principles. I recently retired from the University, but am still active as an Emeritus professor and work part time as Director of Biosciences for hypothes.is, a non-profit tech organization developing technology to annotate the web and a founder of SciCrunch.com, a tech startup that is developing data services for scientific publishing.
Synopsis: The Resource Identification Portal was created in support of the Resource Identification Initiative, which aims to promote research resource identification, discovery, and reuse. The portal offers a central location for obtaining and exploring Research Resource Identifiers (RRIDs) - persistent and unique identifiers for referencing a research resource. A critical goal of the RII is the widespread adoption of RRIDs to cite resources in the biomedical literature and other places that reference their generation or use. RRIDs use established community identifiers where they exist, and are cross-referenced in our system where more than one identifier exists for a single resource.
Recording Available: https://youtu.be/nzy6A5v1-gM
Biography: Director of the Division of Neuroinformatics at the Child and Adolescent Neurodevelopment Initiative (CANDI) and Professor of Psychiatry at the University of Massachusetts Medical School. He has extensive expertise in the development of image analysis techniques and was a co-founder of the Center for Morphometric Analysis (CMA) at Massachusetts General Hospital. In addition, David is a founding editor of the journal Neuroinformatics.
Synopsis: Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) is currently a free one-stop-shop collaboratory for science researchers that need resources such as neuroimaging analysis software, publicly available data sets, or computing power. Since its debut in 2007, NITRC has helped the neuroscience community to use software and data produced from research that, before NITRC, was routinely lost or disregarded, to make further discoveries. NITRC provides free access to data and enables pay-per-use cloud-based access to unlimited computing power, enabling worldwide scientific collaboration with minimal startup and cost. With NITRC and its components—the Resources Registry (NITRC-R), Image Repository (NITRC-IR), and Computational Environment (NITRC-CE)—a researcher can obtain pilot or proof-of-concept data to validate a hypothesis for a few dollars.
Recording Available: https://youtu.be/mpw6N9iZjfU
Biography: Subha Sivagnanam is the Co-PI of the Neuroscience Gateway (NSG). She is also the main software architect of NSG. She works for the Data Enabled Scientific Computing (DESC) division at the San Diego Supercomputer Center and has been working on various HPC projects since 2005.
Synopsis: The Neuroscience Gateway (NSG) facilitates access and use of National Science Foundation (NSF) High Performance Computing (HPC) resources by neuroscientists. Computational modeling of cells and networks has become an essential part of neuroscience research, and investigators are using models to address problems of ever increasing complexity, e.g. large scale network models and optimization or exploration of high dimensional parameter spaces. The NSG will catalyze such research by lowering or eliminating the administrative and technical barriers that currently make it difficult for investigators to use HPC resources. It will offer free computer time to neuroscientists acquired via the supercomputer time allocation process managed by the Extreme Science and Engineering Discovery Environment (XSEDE) Resource Allocation Committee (XRAC). The NSG provides access to the popular computational neuroscience tools installed on various HPC resources through a web portal and programmatic access.
Recording Available: https://youtu.be/2O7AstGdQUo
Biography: My research lies at the intersection of bioinformatics and neuroscience, with a focus on genomics. Please see the lab page for more information.
Synopsis: Genomics applications in neuroscience are being dramatically impacted by new technologies that resolve features at the cell type or single cell level. In this webinar, Dr. Pavlidis will describe tools his lab has created to increase the availability and utility of brain transcriptomes, focusing on the cell-type resolved database NeuroExpresso (http://neuroexpresso.org/). We'll discuss how cell-type based expression can be used to help decipher patterns in transcriptomes obtained from mixed-cell-type samples from postmortem human brain ("bulk tissue"), introducing computational tools accessible in the R statistical computing environment. A preprint describing the NeuroExpresso project is available at http://www.biorxiv.org/content/early/2017/05/18/089219.
Synopsis: Join us as we listen to Dr. Armañanzas in a webinar about NeuroMorpho.Org and related topics. NeuroMorpho.Org is a centrally curated inventory of digitally reconstructed neurons. It contains contributions from dozens of laboratories worldwide and is continuously updated as new morphological reconstructions are collected, published, and shared. The goal of NeuroMorpho.Org is to provide free access to all available neuronal reconstruction data in the neuroscience community.
Biography: Rubén Armañanzas (a.k.a. Ruben Armananzas) obtained his Ph.D. in Biological Computation in 2009 from the University of the Basque Country (Spain). He moved to Madrid to work within the Blue Brain Project at the Technical University of Madrid until fall 2013. He is currently a research faculty member at the Krasnow Institute for Advanced Study of George Mason University, VA. His research topics are machine learning, computational neuroscience, and data science in life sciences. Applications within these topics include automatic classification of neuronal types, knowledge discovery from digital neuronal reconstructions, complex neuromorphic networks, and biomedical analyses of neurological conditions' data. @RbnArma
Recording Available: https://youtu.be/ubLNSVD8rBk
Biography: Dr. Crook earned her PhD in Applied Mathematics at the University of Maryland at College Park and performed her dissertation research with John Rinzel at the Mathematical Research Branch of the National Institutes of Health where she developed coupled oscillator models for cortical dynamics in collaboration with Bard Ermentrout at the University of Pittsburgh. She then held a postdoctoral appointment at the Center for Computational Biology at Montana State University with John Miller and Gwen Jacobs, where she did joint work in neurophysiology, modeling, and neuroinformatics. Dr. Crook now holds a joint appointment between the School of Mathematical and Statistical Sciences and the School of Life Sciences at Arizona State University, where she uses computational approaches to study the dynamics of neurons and neuronal networks and the mechanisms underlying plasticity due to trauma, learning, or disease. Dr. Crook also contributes to the development of NeuroML, an international effort to create a common standard for describing computational models for neuroscience research.
Synopsis: Computational models provide a framework for integrating data across spatial scales and for exploring hypotheses about the biological mechanisms underlying neuronal and network dynamics. However, as models increase in complexity, additional barriers emerge to the creation, exchange, and re-use of models. Successful projects have created standards for describing complex models in neuroscience and provide open source tools to address these issues. Here I provide an overview of these projects and make a case for expanded use of resources in support of reproducibility and validation of models against experimental data.
Biography: Dr. Elam is the scientific outreach lead for the Human Connectome Project and Connectome Coordination Facility based at Washington University School of Medicine in St. Louis, under HCP Co-PI Dr. David Van Essen. Dr. Elam organizes the annual HCP educational course, creates project documentation, and assists users in finding information, navigating, and using HCP data and software tools, including the Connectome Workbench software platform and the new BALSA database for sharing reference and user-submitted brain maps and data.
Synopsis: The Human Connectome Project (HCP) originated as an effort to collect, process, and share advanced multimodal neuroimaging, extensive behavioral, and genetic data from 1,200 healthy adults (HCP Young Adult, ages 22-35) with the goal to comprehensively map region-to-region brain connections and variability in normal individuals. The HCP consortium has recently expanded to apply similar protocols across the lifespan to 1300+ children/adolescents (HCP Development , ages 5-21) and 1500+ older adults (HCP Aging, ages 36-100+). As with HCP Young Adult, all data, methods, and tools for acquisition, processing, analysis, and visualization are being freely released to the scientific community through the Connectome Coordination Facility (CCF). The CCF will also provide access to data gathered through the Baby Connectome Project (ages 0-5) and the 14 Connectomes Related to Human Disease projects.
In the webinar, Dr. Elam will talk about the overall structure and goals of the projects, how users get access to the data, where to find more information and help, highlight some of the advances already achieved, and briefly demonstrate some of the tools being developed, including the Connectome Workbench software platform and the new BALSA database for sharing brain maps and data.
Recording Available: https://youtu.be/uGSgmY8IJ2M
Biography: Dr. Lloyd is a veterinarian and research scientist with expertise in embryo manipulation, genome-wide mutagenesis, and comprehensive phenotyping of the laboratory mouse. His primary research focuses on development of mouse models of human disease, genome editing (e.g., CRISPR), and preservation and resuscitation of genetically altered mice. Dr. Lloyd serves as Director of the UC Davis Mouse Biology Program and PI of the MMRRC at UC Davis.
Synopsis: The MMRRC archives, cryopreserves, and distributes scientifically valuable genetically engineered mouse strains and mouse ES cell lines for the genetics and biomedical research community. We are a national network of archiving, breeding and distribution repositories plus an information, coordinating, and customer-service center serving together as NIH's premier repository of spontaneous and induced mutant mouse and cell lines. The MMRRC is supported by the National Institutes of Health.
Recording Available: https://youtu.be/IpevlgQetVE
Biography: Michael Feolo is a staff scientist at the NIH’s National Center for Biotechnology Information, and since 2007 has been the team lead for the database of Genotypes and Phenotypes (dbGaP). The dbGaP is a database designed to allow researchers public access to questionnaires, protocols, methods, phenotypes, genotypes and the results of association and linkage analyses in whole genome case/control and longitudinal studies of heritable disease. Since 2005, Michael is also team lead for the dbMHC, database, a web interface and permanent public archive of genotype, phenotype, typing kit, and clinical outcome data concerning the variations in the HLA genes located in a region on human chromosome 6 known as the Major Histocompatibility Complex (MHC). Prior to leading the dbGaP team, 2000-2007, Michael worked on developing dbSNP, NCBI’s database of genetic variation. During this time, Michael participated as a member of the International HapMap planning and analysis committees and coordinated the upload of genotype data from the project to the dbSNP. Michael received a BS in Molecular Biology, 1996, and MS in Medical Informatics, 1999, from the University of Utah, Department of Biomedical Informatics.
Synopsis: The database of Genotypes and Phenotypes (dbGaP) was developed to archive and distribute the data and results from studies that have investigated the interaction of genotype and phenotype in Humans.
Recording Available: https://youtu.be/XH94VJBXyxk
Biography: Maryann Martone received her BA from Wellesley College in Biological Psychology and Ancient Greek and her Ph. D. in Neuroscience from the University of California, San Diego. She is a professor Emerita at UCSD, but still maintains an active laboratory She started her career as a neuroanatomist, specializing in light and electron microscopy, but her main research for the past 15 years focused on informatics for neuroscience, i.e., neuroinformatics. She led the Neuroscience Information Framework (NIF), a national project to establish a uniform resource description framework for neuroscience, and the NIDDK Information Network (dknet), a portal for connecting researchers in digestive, kidney and metabolic disease to data, tools, and materials. She is Editor-in-Chief of Brain and Behavior, an open access journal, and on the editorial board of Nature Scientific Data, Frontiers in Neuroinformatics and Journal of Neuroinformatics. Dr. Martone is past President of FORCE11, an organization dedicated to advancing scholarly communication and e-scholarship and currently serves as the chair of the Council on Training, Science and Infrastructure for the International Neuroinformatics Coordinating Facility. Since retiring, she has served as the Director of Biological Sciences for Hypothesis, a technology non-profit developing an open annotation layer for the web and founded SciCrunch, a technology start up based on technologies developed by NIF and dkNET.
Synopsis: Annotation -- from personal note-taking to structured knowledge creation -- is fundamental to biomedicine. Hypothes.is (https://web.hypothes.is/) has developed the capability to add interactive and machine-searchable annotations to any web resource. Annotation, particularly scholarly annotation, is distinct from current commenting systems in that it is anchored to a specific portion of a research object, i.e., a statement, an object in an image, a gene sequence and located according to the physical particulars of the target, i.e., the margin, image coordinates.
Web annotation provides a powerful new capability to biomedicine. With Hypothes.is, any content on the web can be turned into an interactive forum for on-line discussions or annotated with additional information. Because Hypothes.is is engineered for the web, annotations can be replied to, shared and searched across contexts. Hypothesis supports public, private and group annotation.
The implications of this technology are profound for collaborative creation of knowledge across many domains, including journalism, government, education and research. In biomedicine, Hypothes.is provides an independent communication channel on top of the scientific literature where additional information can be added to otherwise static artifacts. It provides a lightweight interactive tool for peer review, education and biocuration. Annotations are tied to article DOI’s, so that annotations will sync across the same article in different locations, e.g., the publisher’s web site, a pdf and Pub Med Central. Through direct linking, annotations can be shared, and the recipient will be taken directly to the annotation in context. Through these capabilities, Hypothesis is laying the foundation for next generation referencing systems.
In this presentation, I provide an overview of the technology and show how Hypothesis is being used within biomedicine.
Recording Available: https://www.youtube.com/watch?v=aR7RJOfjGJs&t=1s
Biography: Robert (Rob) W. Williams received a BA in neuroscience from UC Santa Cruz (1975) and a Ph.D. in physiology at UC Davis with Leo M Chalupa (1983). He did postdoctoral work in developmental neurobiology at Yale with Pasko Rakic and moved to the University of Tennessee in 1989. He is chair of the Department of Genetics, Genomics and Informatics at UTHSC. Williams holds the UT Oak Ridge National Laboratory Governor’s Chair in Computational Genomics. He was a past president of the International Society for Behavioural and Neural Genetics and founding director of the Complex Trait Community (www.complextrait.org). He is editor-in- chief of Frontiers in Neurogenomics, and serves on the editorial boards of Genes, Brain & Behavior, Neuroinformatics, Mammalian Genome, Molecular Vision, European Journal of Anatomy, Alcohol, BiomedCentral Neuroscience, the Journal of Biomedical Discovery and Collaboration, and Behavior Genetics. One of Williams’ more notable contributions is in the field of systems genetics and expression genetics (eQTL analysis). He and his research group have built GeneNetwork (www.genenetwork.org), an online resource and suite of gene mapping code that is used widely by the genetics and molecular biology communities.
Synopsis: Technical and computational barriers prevent researchers and clinicians from incorporating more powerful genomic methods in addiction research. The purpose of the new NIDA P30 Core Center of Excellence in Omics, Systems Genetics, and the Addictome is to empower researchers to analyze genetic, epigenetic and environmental causes of drug abuse risk, relapse, and treatment. We are doing this by assembling many omics resources—primarily for rat, mouse and human—that can give investigators mechanistic and behavioral insights into addiction. In addition, we provide local workshops in systems genetics and advanced computational/statistical modeling for NIDA research teams.
Recording Available: https://youtu.be/GufOXv386oQ
Biography: Amos Bairoch is a Swiss bioinformatician and Professor of Bioinformatics at the Department of Human Protein Sciences of the University of Geneva where he leads the CALIPHO group at the Swiss Institute of Bioinformatics (SIB) combining bioinformatics, biocuration, and experimental efforts to functionally characterize human proteins. Until June 2009, Amos headed the Swiss-Prot group which develops the UniProtKB/Swiss-Prot knowledgebase which he created in 1986 as well as the PROSITE and ENZYME databases. He was also co-responsible for the development of ExPASy, the world's first website dedicated to protein molecular biology. Currently his main activities are focused on the development of neXtProt, a web knowledge platform on human proteins and of the Cellosaurus. Amos Bairoch has been awarded several distinctions, among which the European Latsis Prize, the Otto Naegeli Prize and the HUPO Distinguished Achievement Award. He is an ISCB Fellow.
Synopsis: The Cellosaurus (https://web.expasy.org/cellosaurus/) is a knowledge resource on cell lines. The aim of this webinar is to describe the content of the Cellosaurus but also to discuss some issues mundane to cell lines especially misidentification/contamination, naming problems as well the lack of standardization of the information reported by cell line collections/companies. We will also describe our collaboration with ICLAC (http://iclac.org/) and our involvement in the Resource Identification Initiative (https://www.force11.org/group/resource-identification-initiative).
Recording Available: https://youtu.be/26S268OQ084
Biography: Currently the Research Assistant Professor at Psychology and Brain sciences department at Dartmouth, leading the Center for Open Neuroscience, Dr. Yaroslav O. Halchenko holds a Ph.D. in Computer Science from the New Jersey Institute of Technology and got post-doctoral training at Dartmouth College. He is a neuroimaging research scientist, an official Debian developer, a member of INCF neuroimaging task force, and a lead of PyMVPA, NeuroDebian, DataLad and other projects. With the goal of contributing to our understanding of the brain function, Dr. Halchenko is interested in developing new and formalizing existing analysis methodologies and software solutions in the domain of computational and cognitive neuroscience.
Biography: Satrajit Ghosh (http://satra.cogitatum.org/) is a Principal Research Scientist at the McGovern Institute for Brain Research at MIT and an Assistant Professor in the Department of Otolaryngology at Harvard Medical School. He is also the Director of Data Models and Integration project of ReproNim, an NIH P41 Center for Reproducible Neuroimaging Computation. His research interests span computer science and neuroimaging, specifically in the areas of applied machine learning, software engineering, and applications of neuroimaging. The primary focus of his research group is to develop knowledge discovery platforms by integrating a set of multidisciplinary projects that span precision medicine in mental health, imaging genetics, machine learning, and dataflow systems for reproducible research. He is a lead architect of the Nipype dataflow platform, an ardent proponent of decentralized and distributed Web solutions for data sharing, querying, and computing, and a strong believer in solving problems through collaboration and crowd-sourcing.
Synopsis: In recent years there has been an explosion of technology platforms, analysis software, and imaging and other data. This talk will highlight a set of platform technologies, software, and data collections that close and shorten the feedback cycle in research. While many of these technological advancements have transformed our group's research approaches and questions, their limited exposure across the domain of neuroscience indicates a large gap in the current education of neuroscientists in connecting questions to relevant data and tools. To counter this deficit, we have been working on a set of collaborative initiatives to create resources that support the entire life cycle of experimental research and promote the importance of making scientific research "open by design".
Recording Available: https://youtu.be/9cEvh1X2iiE
Dr. Elissa J. Chesler: Dr. Chesler is a professor at The Jackson Laboratory in Bar Harbor, Maine, where she works on the development of tools and resources for integrative genetics and genomics with an emphasis on their application in behavioral genetics. She is the Director of the NIDA Center for Systems Neurogenetics of Addiction and has led the GeneWeaver project since its inception in 2006 as “The Ontological Discovery Environment”.
Dr. Erich J. Baker: Dr Baker is a professor of Computer Science at Baylor University. He has been involved in the development of the GeneWeaver web application since its inception.
Synopsis: GeneWeaver is a web application for the integrated cross-species analysis of functional genomics data to find convergent evidence from heterogeneous sources. The application consists of a large database of gene sets curated from multiple public data resources and curated submissions, along with a suite of analysis tools designed to allow flexible, customized workflows through web-based interactive analysis or scripted API driven analysis. Gene sets come from multiple widely studied species and include ontology annotations, brain gene expression atlases, systems genetic study results, gene regulatory information, pathway databases, drug interaction databases and many other sources. Users can retrieve, store, analyze and share gene sets through a graded access system. Analysis tools are based on combinatorics and statistical methods for comparing, contrasting and classifying gene sets based on their members. An overview of the database and tools will be presented along with applications in alcohol and addiction biology. GeneWeaver is supported by NIH R01 AA18776, jointly funded by NIDA and NIAAA. Additional support comes from the Center for Precision Genetics, NIH U54 OD 020351.
Recording Available: https://youtu.be/Vq7aZWNLM4c
Biography: Dr. Sarala Wimalaratne is the Project Lead for the Identifiers.org system. She envisions, implements and manages the Identifiers.org system. She has a Software Engineering degree and a PhD in Bioengineering. Sarala has been involved in many different data integration and infrastructure projects over the past 8 years at the EMBL-EBI. She is actively involved in the Data Commons Pilot Phase Consortium on globally unique identifiers (GUIDs), the Elixir Interoperability Platform on BioSchemas and Identifiers, the FORCE11 Data Citation Implementation Pilot on Identifiers and the EU FREYA Project on identifier services.
Synopsis: The Identifiers.org system is a central infrastructure for findable, accessible, interoperable and re-usable (FAIR) data. It provides a range of services to generate, resolve and validate persistent Compact Identifiers to promote the citability of individual data providers and integration with e-infrastructures.
The Identifiers.org registry contains hundreds of manually curated, high quality data collections, with each assigned a unique prefix. A combination of the prefix and a locally assigned database identifier (accession) forms a Compact Identifier, [prefix]:[accession]. The Identifiers.org resolver provides a stable resolution service for these Compact Identifiers, taking into consideration information such as the uptime and reliability of all available hosting resources. For example, pdb:2gc4, GO:0006915, doi:10.1101/101279, orcid:0000-0002-5355-2576 etc. In addition, we have formally agreed with N2T resolver, based in California Digital Library to share a common prefix registry. This enable users to resolve Compact Identifiers using Identifiers.org (https://identifiers.org) or N2T (https://n2t.net/) resolvers. As Compact Identifiers and the resolving mechanisms of identifiers.org are generic, identifiers.org aligns well with other identifier systems and emerging requirements in the PID ecosystem.
Recording Available: https://youtu.be/YauhbzNusAk
Biographies: Dr. Molly Bogue is a Research Scientist at The Jackson Laboratory in Bar Harbor, Maine. She is Principal Investigator of the Mouse Phenome Database project. Her interests include research replicability in preclinical research and sex differences.
Dr. Elissa Chesler is currently an Associate Professor of Bioinformatics and Computational Biology at The Jackson Laboratory in Bar Harbor, Maine. She holds a Doctor of Philosophy in Neuroscience from the University of Illinois at Urbana-Champaign. Her laboratory integrates quantitative genetics, bioinformatics and behavioral science to understand and identify the biological basis for the relationships among behavioral traits.
Synopsis: The Mouse Phenome Database (MPD), in existence since 2001, provides access to primary experimental trait data, genotypic variation, protocols and analysis tools for mouse genetic studies. Data are contributed by investigators worldwide and represent a broad scope of phenotyping endpoints and disease-related traits in naïve mice and those exposed to drugs, environmental agents or other treatments. MPD ensures rigorous curation of phenotype data and supporting documentation using relevant ontologies and controlled vocabularies. As a repository of curated and integrated data, MPD provides a means to access/re-use baseline data, as well as allows users to identify sensitized backgrounds for making new mouse models with genome editing technologies, analyze trait co-inheritance, benchmark assays in their own laboratories, and many other research applications. MPD’s primary source of funding is NIDA. For this reason, a majority of MPD data is neuro- and behavior-related. In this webinar, we will explore new tools and features of the recently re-implemented MPD with emphasis on neuro-behavior examples.
Recording Available: https://youtu.be/T-_yo1H0CIo
Biography: Holding a Ph.D. in Computational Neuroscience from The Technical University in Berlin, Dr. Hauke Bartsch has been responsible for software developments in the areas of diffusion tensor imaging, brain perfusion, whole slice image processing and reconstruction, brain mapping and atlas generation, deformable shape models, shape analysis and general numerical simulations. Currently working as a Programmer Analyst in the Department of Radiology at the University of California, San Diego, Dr. Bartsch plays a key role in the development of the data exploration and hypothesis testing portal (Data Portal) used, for example, in the Pediatric Imaging Neurocognition and Genetics (PING) study, the Alzheimer's Disease Research Center (ADRC) project, and in the Pediatric Longitudinal Imagine Neurocognition and Genetics (PLING) study. Recently the system was also adapted for the Human Connectome Project (HCP).
Synopsis: The Red Queen said to Alice, "If you want to get somewhere else, you must run at least twice as fast as that!”. In the age of big data science, data collection, study observation and data sharing have to change their ways to keep up with ever increasing numbers of study participants, time points and the shortening of intervals of data sharing. Dr. Hauke Bartsch will present some key features of the ABCD studies collection of biological and behavioral brain phenotypes with a special focus on data visualization. During the presentation we will see how one of a kind research studies benefit from best practices of software development and how transparency, interactivity and gamification can be used to improve data quality by increasing the acceptance and utilization of our computer systems by all users.
Recording Available: https://youtu.be/2fI3tNUGGQ8
Biography: Dr. Sinu Paul is a bioinformatics scientist at the Immune Epitope Database and Analysis Resource Project located at the La Jolla Institute for Allergy & Immunology in San Diego, California. His work is mainly focused on development of computational algorithms and tools using machine learning techniques and statistical applications for application in immunology such as immune epitope prediction and analysis of epitope related data.
Synopsis: The IEDB Analysis Resource (IEDB-AR, http://tools.iedb.org) hosts a collection of tools for the prediction and analysis of immune epitopes. Epitopes are peptides derived from antigens and recognized by T cells which in turn result in generation of immune response. Identification of epitopes is important in several areas such as vaccine discovery, development of diagnostics and removal of unwanted immune responses against protein therapeutics. Experimental identification of epitopes can be laborious and time consuming. Therefore computational prediction tools are used nowadays to select epitope candidates. The IEDB-AR provides several methods for prediction of MHC class I and MHC class II binding affinity, antigen processing, immunogenicity and B cell epitopes as well as tools for analysis of epitope related data. The talk will give an overview of important tools available at IEDB-AR and brief descriptions on how to use them and interpret the results.
To Join: At the time of the conference click this link https://uchealth.zoom.us/j/458918439
Start Time: 11AM PST / 2 PM EST
Biography: Stephen Larson is the CEO of MetaCell, global leaders in neuroscience software, with clients ranging from top-20 academic institutions to big pharma. He is a co-founder of the international OpenWorm project that is constructing a detailed digital simulation of a whole animal in an open science fashion.
He has co-developed a patent, presented at more than two dozen forums and published over a dozen articles in academic journals such as Nature and Frontiers in Neuroscience. Stephen’s work has been featured in the Economist, the New York Times, Wired, the Atlantic, at two TEDx forums and a Science Channel show with Morgan Freeman.
He holds a Bachelor and Masters from MIT in Computer Science with a focus on Artificial Intelligence and received a PhD in Neuroscience from the University of California, San Diego.
Synopsis: The modern neuroscience researcher or neurotech company faces a challenging landscape in order to use experimental or device data to its maximal potential. While data collection and accumulation are expanding, approaches to data management and insight gathering still fall short.
In this free, open webinar we’ll be discussing how three major activities - 1) visualize, 2) collaborate, and 3) build - can massively expand an organization's ability to extract value from neuroscience data and work with it on the internet.
The webinar (45 mins + Q&A) will feature online interfaces and showcase the technological landscape available to solve this challenge and drive the neuroscience research industry forward.
Recording available: https://www.youtube.com/watch?v=p97toNNcVrw&t
Start Time: 11 AM PST/ 2 PM EST