# Xenbase - Tech Development

> **NIH NIH P41** · CINCINNATI CHILDRENS HOSP MED CTR · 2021 · $223,653

## Abstract

Component: TECHNOLOGY DEVELOPMENT
PROJECT SUMMARY/ABSTRACT
The Technology Development component describes software development for Xenbase. This
includes code in the database, web applications, user and curator interfaces. New data types and
new curation efforts require new systems, tools and software interfaces to be built. Importantly,
interfaces must be designed to allow our community members to browse and interrogate the data
via our web portal. We have recently added many new content types to Xenbase, including RNA-
seq and ChIP-seq data from GEO, and anatomical and expression phenotypes; and there are
many additional types of content that will require support from technology development team,
including single-cell omics, clustering tools for omics visualization, tolls to visualize human
disease variants and Xenopus phenotypes. As many of the biologists generating and accessing
these data are not bioinformaticians, we need to develop tools and interfaces that are intuitive
and easy to use. An excellent example of how we achieved this is our recently released GEO
module that allows non-experts to view, interact with, and understand RNA-seq data through a
simple, intuitive and interactive web interface. Over the next five years, we will proceed through
numerous steps for each new to type of data we aim to support: assessing data requirements,
data modeling, middleware software development, testing and optimization of trial releases,
develop curator, user and data browsing interfaces. Prioritization of projects is done in
consultation with the Xenopus research community via annual surveys and workshops at
conferences, input from our external advisory board and collaborators, and, in the future, in
consultation with the Alliance of Genome Resources (AGR) workgroups. Planned new projects
include ATAC-seq data from GEO, orthology data from DIOPT, single-cell RNA-seq, support for
human disease variants and single-cell omics. Technology Development will also support our
increased use of machine learning as applied to Xenopus literature curation.
Aim 1: Support expanded and novel content.
Aim 2: Generate custom content and support variants and single-cell datasets via external
resources.
Aim 3: Interface with external resources.

## Key facts

- **NIH application ID:** 10169895
- **Project number:** 2P41HD064556-11
- **Recipient organization:** CINCINNATI CHILDRENS HOSP MED CTR
- **Principal Investigator:** Aaron M Zorn
- **Activity code:** P41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $223,653
- **Award type:** 2
- **Project period:** 2010-06-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10169895

## Citation

> US National Institutes of Health, RePORTER application 10169895, Xenbase - Tech Development (2P41HD064556-11). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10169895. Licensed CC0.

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