The class is free but registration is required.
You can register at https://hpc.nih.gov/nih/classes/

This introductory course teaches the basics of deep learning and of different types of deep learning networks through a set of hands-on biological examples implemented in Keras, one example per class. Class #1 will provide an introduction to the Deep Learning with Keras, and then focus on Convolutional Neural Networks as applied to semantic segmentation of bioimages.

Expected knowledge: Basic Python, Basic Linux/Unix

This class is part of a series, but each class is stand-alone. The class will be webcast.

Instructor: Gennady Denisov (NIH HPC staff)

ZoomGov link for all the individual meetings and the seminar:
https://nih.zoomgov.com/j/1619988709?pwd=dEIwM0ExOXFtSjNqd0xmcGJCVEk5QT09
Meeting ID: 161 998 8709
Passcode: 20892

Presenter:

Cole Trapnell, Ph.D.
Associate Professor
Department of Genome Sciences
University of Washington

Please mark your calendars for our next seminar by Cole Trapnell. He is a familiar name to most genomics researchers, and he actually spent his early years in Maryland. Please note that we are returning to our afternoon time (seminar info below). There are a few openings for a one-on-one meeting with him after his talk. Let me know if you’d like one. Postdocs and students are welcome to join the fellows tea with the speaker right after his talk in the same zoom link as the talk (send me RSVP for my count).

Cole Trapnell developed many widely used bioinformatics tools including TopHat, Cufflinks, Bowtie, and Monocle. His group has also co-developed, along with Jay Shendure’s lab, a scalable workflow for single-cell genomics called “combinatorial cellular indexing”. They recently used this approach to construct a transcriptional atlas for the C. elegans nematode and profile organogenesis in the mouse at whole-embryo scale.

Myong-Hee Sung, Ph.D.
Earl Stadtman Investigator
Chief, Transcription Systems Dynamics and Biology Unit
Laboratory of Molecular Biology and Immunology
National Institute on Aging
NIH
251 Bayview Boulevard, Room 06C226
Baltimore, MD 21224

Office: 410-558-8475
email: sungm@mail.nih.gov

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This course provides detailed information on managing and sharing data from the first data planning stage, through the data life cycle, to data archiving, and finally to selecting an appropriate repository for data preservation. By the end of this course, participants will have an understanding of data management best practices, data management tools, and resources that enable data sharing.
This is an introductory two-part course for those who want to learn about research data management and sharing, or for those who are interested in a refresher. Part 1 of this training will cover understanding research data, how to manage research data, and how to work with data. Audience: Researchers, fellows, post-docs, and trainees. You must register separately for Part 2 of this class.

Register

This course provides detailed information on managing and sharing data from the first data planning stage, through the data life cycle, to data archiving, and finally to selecting an appropriate repository for data preservation. By the end of this course, participants will have an understanding of data management best practices, data management tools, and resources that enable data sharing.
This is an introductory two-part course for those who want to learn about research data management and sharing, or for those who are interested in a refresher. During Part 2 of this training, participants will learn about sharing and archiving data. Audience: Researchers, fellows, post-docs, and trainees. You must register separately for Part 1 of this class.

Register

Session Description

Learn how to get started on using QIAGEN’s Ingenuity Pathway Analysis (IPA) to quickly identify biological relationships, mechanisms, pathways, functions and diseases most relevant to experimental datasets. IPA is cited in tens of thousands of peer-reviewed articles. The class will demonstrate how to explore IPA’s knowledge & discovery tools to relate the most recent literature findings to your research. The demo session will mainly focus on biological interpretation of expression data but will also cover multi-omics analysis including variant data and phosphoproteomics.

Getting Started: fundamentals of IPA; overview of key features; search & pathway building; advanced search; building & editing pathways; using Build & Overlay tools. Dataset Analysis: data upload & analysis; interpretation of gene, transcript, protein & metabolite data; pathway analysis & canonical pathways; downstream effects & interpreting the heat map; causal regulators and their directional effect on genes, functions and diseases across multiple time points or doses; interpreting networks; comparison & multiple observations analysis; miRNA and isoform analysis; BioProfiler: define relationships between molecule activity and diseases/processes in the literature. Q & A session: A QIAGEN Ingenuity Field Applications Scientist will be available to answer individual questions or discuss specific projects.

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Session Description
Animal models are used to study the development and progression of diseases and to test new treatments. Model organisms are a subset of research organisms that serve as a proxy for understanding human biology. This introductory class will cover techniques on locating biomedical research articles, patents, NIH-funded research projects, genetic information, and print and electronic books related to animal models and model organisms. The class will also discuss the differences between animal models, research organisms, and model organisms, and will review requirements and resources for the NIH Model Organism Sharing Policy.

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Session Description
QIAGEN’s CLC Genomics Workbench enables researchers to analyze NGS data without the use of command line and is a powerful tool for determining differential expression and for variant calling. In this workshop students will explore the usage of CLC Genomics Workbench for taking raw NGS data and performing QC, processing, statistical analyses, and visualizations. The first part of the training will focus on the identifying differentially expressed genes from RNA-seq and how those results can be passed to Ingenuity Pathway Analysis (IPA) for biological interpretation. The second half of the training will provide insight into analysis of DNA-seq data for variant detection and will introduce how Ingenuity Variant Analysis (IVA) can be used to prioritize those variant findings.

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Session Description
This course walks through using and applying two popular, freely available genome browsers and how they can help bioinformatics analysis: the University of California Santa Cruz (UCSC) Genome Browser and the Integrative Genomics Viewer (IGV). Used to view the assembly of the complete genome in human or other species, these browsers are valuable tools for identifying and localizing genes/mutations. This course will demonstrate how to view different genome maps/tracks and make best use of them.

Feel free to install the IGV browser in advance from here – https://software.broadinstitute.org/software/igv/download(link is external) (the UCSV browser is web browser based).

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Session Description
QIAGEN’s CLC Genomics Workbench enables researchers to analyze Next Generation Sequencing (NGS) data without the use of command line and is a powerful tool for processing microbial data. In this workshop students will explore how the Microbial Genomics Module can be utilized for taxonomic profiling of sample microbiomes using both amplicon and whole metagenome sequencing data, including generating statistical results and visualizations. The workflows for de-novo genome assembly and annotation will also be presented.