When submitting data to the Gene Expression Omnibus (GEO), you must submit three types of files: raw data files, processed data files and a metadata spreadsheet. At the beginning of this year, I wrote a blog article titled “Tips for Submitting RNA-seq Data to GEO” where I provided guidance on submitting the raw data files [Read more]
I previously wrote a blog titled “NIH DMS Plan Format Updates, 2026 Edition: What to Know” on March 27, 2026, before the new 2026 Data Management and Sharing (DMS) Plan format took effect on May 25, 2026 (NOT-OD-26-046). This blog post builds on that earlier article by providing additional clarifications, implementation guidance, and newly available [Read more]
What happens when you mix analysts, clinical research staff, directors, PhD students, marketing leaders, agile operations managers, and add walk-up songs and a Party Rocker? You get the first-ever DMS Trivia Challenge at Love Data Week 2026. Hosted by the Becker Data Management and Sharing (DMS) Team, the event brought together 11 teams representing roles [Read more]
The National Institutes of Health (NIH) will implement an updated format for Data Management and Sharing Plans (DMSPs) effective May 25, 2026 (NOT-OD-26-046). While the underlying 2023 NIH Data Management and Sharing Policy remains unchanged, this new format reflects NIH’s broader effort to reduce administrative burden and improve consistency in how plans are written, reviewed, [Read more]
Are you new to Python programming? Python is a free open-source programming language that supports multiple approaches to programming including object-oriented programming, scripting and automation. It is widely used for web development, data science and machine learning. Whether your goal is data analysis, building applications, or automating tasks, python offers an extensive library ecosystem and [Read more]
We have received several inquiries about depositing RNA-seq data generated by WashU’s Genome Technology Access Center (GTAC) into the Gene Expression Omnibus (GEO) repository managed by the National Center for Biotechnology Information (NCBI). As a result, it is a good time to write a blog article providing guidance on this issue for researchers on campus. [Read more]
Research continues to generate more and more data, and large-scale data analyses can be complicated, computationally intensive and not suitable for personal computers. When faced with such a problem, what options do researchers have? Researchers can use High Performance Computing (HPC), a powerful technology which makes use of multiple computing processors that work in parallel [Read more]
In recent years, there has been exponential growth in the use of machine learning (ML) in the life sciences, fueled by increased access to powerful hardware (e.g., GPUs) and high-quality FAIR biodata enabled by the open science movement. One standout example is AlphaFold, which uses ML to predict protein structure from genetic sequences, a breakthrough [Read more]
In the first two parts of this blog series, I introduced the main player in the proteomics data repository ecosystem, the ProteomeXchange (PX) Consortium. Outside of the PX Consortium, there are an additional handful of repositories holding proteomics data. These additional repositories serve special cases or certain scientific communities, but it may be useful for [Read more]
A plethora of learning resources for bioinformatics and genomics are available on the web, but did you know that you can find a wide variety of free learning resources on campus here at WashU? Do you need to learn fundamentals of bioinformatics and computational genomics? Are you interested in learning more about techniques and tools [Read more]