Course Catalog

What’s the difference between “regular” statistics (i.e. what you may have been using in the past several years) and the “new” Bayesian statistics? Which one should you use for your next study?

This is Part 2 of a two-part lecture series intended for non-statisticians interested in understanding the basic, intuitive thinking behind the two schools of statistical inference: frequentist (known as classical) and Bayesian. Part 2 will address the Bayesian approach, and will cover the concepts of Bayes’ Theorem, prior and posterior distributions, and Bayes factor. Technical details will be kept to an absolute minimum.

Although you may attend only one part of this series, attending both parts will give you a better sense of the contrast between these two statistical approaches. During the class, time will be devoted to questions from attendees and references will be provided for in-depth self-study. You must register separately for Part 1 of this class series.

Tables, charts, and figures are often used to describe and share complex scientific information. However, it can be difficult to determine when it's appropriate to use these visual tools and how to design them effectively. During this session, participants will learn the best practices for creating tables, charts, and figures and how to customize them for specific journal requirements. An overview of design tools and resources will also be provided.

Creating a good scientific poster can be difficult. This class provides participants with tips and best practices to develop an engaging poster that conveys information clearly. This session is a short introduction for those new to creating a scientific poster and a refresher for those more experienced.

Overview

This is an introductory level class for participants to familiarize themselves with Deep Learning concepts and techniques using MATLAB. These techniques can be used to solve complex problems related to images, signals, text and controls. The training session will be held on two days.

Day One

On day one of the training, attendees will become familiar with Deep Learning concepts and techniques using MATLAB Online to train deep neural networks on GPUs in the cloud and create deep learning models from scratch for images and signal data.

Day Two

On day two of the training, attendees will explore pretrained models and use transfer learning. We will touch on how MATLAB can interoperate with other deep learning frameworks as well as automatically generate optimized code for embedded targets. 

Embase is a biomedical and clinical database of bibliographic information. This seminar will explain Embase's features and how it compares to other databases like PubMed.  It will include designing queries, using form-based queries, multiple search strategies, combining searches, and conference and literature coverage. This class was designed for beginners and intermediate NIH users.

Key Pathway Advisor (KPA) is a web application for biological pathway analysis of OMICs data. This session will demonstrate using KPA to: explore the biological meaning of data; predict key protein activity changes that could be the root cause of gene expression alterations; understand how biological pathways are impacted by data; create hypotheses about new targets, mechanisms of action, biomarkers and disease associations; and align results with current knowledge of biomarkers and drug targets. Bioinformatics experience is not required to use this tool.

In this webinar, attendees will learn to call MATLAB from Python and to call Python libraries from MATLAB.  In addition, they will learn how to use MATLAB’s Python integration to improve the compatibility and usability of the code. 

This is an introductory-level class taught by MathWorks. No installation of MATLAB is necessary. 

Biowulf is a Linux cluster designed for large numbers of simultaneous jobs common in the biosciences. It is a powerful tool; one node in Biowulf has more memory than a typical desktop computer. NIH CIT now has a MATLAB site license on Biowulf, so any investigator at the NIH can use MATLAB. In conjunction with the High Performing Computation team, this beginner/intermediate two-hour course covers setting up an account and accessing Biowulf, as well as running MATLAB on Biowulf, from routine beginner MATLAB applications to operating MATLAB on thousands of cores.  

VSClinical is designed for researchers to efficiently process the clinical interpretation of variants based on Association for Molecular Pathology (AMP) and American College of Medical Genetics and Genomics (ACMG) guidelines. This class will review the importance and value of automating the search for available clinical trials for the improvement of cancer treatment and prevention. Attendees will explore content and examples leveraged by VSClinical for site, inclusion criteria, relevant drugs, and matching biomarkers. The following topics will be covered: somatic guidelines inclusion of reporting on clinical trials, NCI source database clinical trial content, automated integration of accessing clinical trial content from VSClinical, and example biomarkers to demonstrate the process to report.

Clinical variant analysis is a three-stage process that entails quality control and processing of data, creating a draft report for cell variant evaluations using different genomic databases and annotation sources, assessing the draft report, and signing-off on the final report. VSClinical is software that uses a single testing paradigm to consolidate and automate the workflow of this three-part analysis. Participants will learn how to use VSClinical to transfer data between different users, evaluate germline and somatic cell variants according to the American College of Medical Genetics (ACMG) and Association for Molecular Pathology (AMP) guidelines, and create clinical reports with the new Word-based templates.

This class introduces version control and how to use GitHub for project versioning. Participants will have a better understanding of version control, GitHub, and their advantages for managing projects.

Upon completion of this class participants should be able to recognize why version control is useful, discuss the difference between Git and GitHub, list the options for authenticating to GitHub, and list the options for creating a personal access token (PAT).

Video is increasingly being used to share scientific information, whether as part of an online conference, educational course, or promotional tool. This class will share tips and tricks for preparing media, capturing high quality images and sound, and ensuring an overall professional appearance. Specific guidance for remote presentations, video abstracts, and audiovisual software and equipment will also be provided.

This class will provide an overview of common Bioconductor datatypes and explore options for working with biological sequence data.  Specifically, this class will focus on the object types for storing and manipulating genomic features and sequences.

Upon completion of this class participants should be able to locate resources on S4Vector classes, understand the standard R datatypes, list the 6 basic Bioconductor classes, and discuss methods for working with biological sequences.

Learn how to write compelling and concise research papers, understand the publishing lifecycle, and become familiar with issues surrounding copyright and plagiarism. The NIH Library offers a variety of classes to enhance your knowledge about scholarly communication and increase your chances of being published.