Improving genome analysis by identifying and annotating repetitive DNA sequences
Official title: Development and Maintenance of RepeatMasker and RepeatModeler
Funded at Institute for Systems Biology · NIH-11042280 · Data updated 2026-11-12
This study is working on improving how we find and label certain repeating parts of DNA in mammals and other organisms, which is important for understanding their genetic makeup and evolution, and it's designed for scientists who want to make genome studies more accurate and reliable.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Institute for Systems Biology NIH-funded |
| Lab location | 1 site (Seattle, United States) |
| Project start | February 4, 2022 |
| Project end | January 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $591,186 |
| NIH project number | 5R01HG002939-19 |
| Project ID | NIH-11042280 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for benefiting from this research include individuals with genetic conditions linked to transposable elements or those undergoing genomic sequencing for diagnostic purposes.
✕Less likely to help
Patients who do not have genetic conditions or are not undergoing genomic analysis may not receive direct benefits from this research.
What this research studies
This research focuses on enhancing the identification and annotation of interspersed repeats in mammalian and other eukaryotic genomes, which are crucial for accurate genome sequence analyses. By utilizing tools like RepeatModeler and RepeatMasker, the project aims to develop methods for uncovering and reconstructing transposable elements (TEs) that have significant impacts on genome activity and evolution. The research addresses the challenges posed by the explosive growth in sequenced species and aims to improve the quality and consistency of genome annotations through better computational methods and curation processes.
Why it matters
Potential benefit: If successful, this research could lead to more accurate genome analyses, benefiting patients by improving our understanding of genetic diseases and evolutionary biology.
How similar studies have gone: Other research has shown success in improving genome analysis through similar computational approaches, indicating a promising avenue for advancements in this field.
Where this research is happening
-
Institute for Systems Biology
Seattle, United States Active
Researchers
- Principal investigator: Smit, Arian Fredericus Anthonius — Institute for Systems Biology
- Study coordinator: Smit, Arian Fredericus Anthonius
Related research
Other NIH-funded projects on the same topics.
-
Digital twin to personalize acute myeloid leukemia treatment
This project builds a virtual copy of an adult's AML using their blood and bone marrow data so doctors can try out treatment options on the model before giving them to the patient.
-
Personalized digital models for acute myeloid leukemia
This project creates a computer model of a person's AML from their blood and bone marrow data so doctors and patients can explore which treatments might work best.
-
Understanding how Bacteroides fragilis changes affect phage therapy
Researchers will study how a common gut bacterium changes its surface and defense features to evade phages, with the goal of improving phage-based treatments for infections and related diseases.
-
AI-powered cancer data hub to map tumor risk and treatment responses
A cancer-focused project will build an AI-driven data platform that combines genomic, transcriptomic, proteomic, and spatial data to better understand cancer risk and how tumors respond to treatment.
-
Understanding why some bacteria hide inside cells during infection
A study will look at how a tiny number of Salmonella bacteria inside human cells survive antibiotic treatment by changing both their own genes and the host cell’s gene activity.
-
Tissue imaging and spatial profiling resources for tumor studies
A core research resource helps researchers study tumor tissues with advanced imaging and multi-omic profiling to understand their biology.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.