What is the D-Challenge 2025?
Inviting novice and experienced scientists to apply their skills and passion to dive into pre-existing data and build new models, and posit new hypotheses pertaining to Type 1 Diabetes.
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D-Challenge 2025: What
The D-challenge is an in silico based competition where scientists participate by mining a data set(s) to create a novel hypothesis pertaining to T1D. We have highlighted several high value resources on the “Resources” tab.
- Using the data driven resources and tools, registered D-Challenge participants identify targets that coincide with their interests.
- Using other partnered Resources (see below) D-Challenge participants go deeper into the understanding of how these data may contribute to T1D.
- Using known and newly accessed data resources, challenge participants create a novel hypothesis and Pitch their hypothesis to the JDRF-T1D Fund in a “Pitch Polish” and finally to our community of judges
Some highlights from Joaquin Reyna, 2021 D-Challenge winner, from the La Jolla Institute interview:
- “The beauty of this contest is it is about developing a hypothesis, and it is very open”, you can change directions at any point if your idea is just not making headway
- “My advice is to be fast, focus on your strengths, and pick up on ideas during the weekly meetings. The dkNET can facilitate finding a lot of data sets and resources.”
Check out his interview.
D-Challenge 2025: Who
Participation in the Challenge is open to novice and experienced scientists. We are asking you to share this information broadly within your organization in order to assemble the most robust group of participants and competitors to form a team of up to (6) members. Registration is FREE and is open till September 12th, 11:59 PST.
D-Challenge 2025: Awards
T1D is a multifactorial disease, opportunities abound for participants to be creative and bold in coming up with hypotheses to submit for a $10,000.00 prize to one team.
D-Challenge 2025: How
dkNET provides a wealth of resources that will be of value to researchers, students, and educators alike. We have created a series of topical webinars and additional tutorials to advance the study and application of FAIR data and bioinformatics tools.
To further expand the offered data driven D-Challenge knowledge base, we have partnered with several well known consortia in both T1D and bioinformatics fields. These resources include: dkNET, T1D Knowledge Portal (T1DKP), Appyters, HIRN, Mouse Metabolic Phenotyping Center (MMPC), Protocols.io, nPOD, PANCREATLAS, PANC-DB, signaling pathways project, AIRR, CalR, and the JDRFT1DFund.
Overview
We are asking cross-functional teams to generate novel hypotheses using rich, curated data sets.
The D-Challenge is a focused scientific movement that begins with the end in mind. We are leveraging our connections with Type 1 Diabetes researchers and inviting ALL of them to compete to catalyze innovation and accelerate research towards a practical cure for Type 1 Diabetes. In doing so, we aim to add a solid appreciation of the biology that drives this relentless disease to the current literature and knowledge base.
Type 1 Diabetes is a multifactorial disease that is studied by many scientific disciplines. the(sugars)science, is partnering with dkNET (the NIDDK Information Network) to bring the full power of on-line digital resources to the challenge of Type 1 Diabetes.
In addition to claiming a $10,000 cash prize, winners will have an opportunity to present their hypothesis and interact with an audience including:
- Academic and institutional luminaries in the fields of Bioinformatics and Type 1 Diabetes research
- Industry leaders in biotechnology
- Professionals and advisors involved in venture funding
dkNET is an information and search portal that helps researchers find research resources relevant to their research and keep up to date on new tools, services, and mandates to support robust and reproducible science. Through our resource catalog, Bionformatics Learning Hub, Hypothesis Center -new computational core, newsletter and webinar series, we connect researchers to resources in digestive, diabetes, and kidney diseases.
Details
The D–Challenge is a community research challenge designed to increase awareness and use of the rich ecosystem of on-line tools and data findable through dkNET to develop a compelling hypothesis about the biology, treatment, or sequelae of Type 1 Diabetes. It is open to participants of all skill levels, from students to skilled bioinformaticians and data scientists.
The goal in this challenge is to bring investigators across disciplines to apply their skills and passion to the problem of T1D: its biology, treatment and sequelae, through the use of a rich interconnected ecosystem of data tools and resources. The extensive resources and tools hosted through dkNET provide the opportunity to catalyze searches for novel pathways implicated in disease pathophysiology and / or identify new therapeutic targets. As a partner in the D–Challenge, dkNET provides access to these resources and tools in an easily available setting, fostering discovery by the broad community of investigators focused on T1D.
Entries will be judged on the creative use of public tools, data, and knowledge resources to develop a compelling hypothesis regarding the biology, treatment, or sequelae of T1D. Participants are expected to use multiple on-line tools and platforms and to develop a plan as to how the hypothesis could be tested. The challenge focuses on in-silico development and testing and will not involve a wet lab component.
This challenge is open globally.
General information
- Registration submissions open until September 12 2025 at 11: 59 pm Pacific Time
- September 19 2025 10 AM PST//1 PM EST: Kick off meeting
- September 26 2025 Submit LOI (non-binding)
- September 26-October 17 2025 10 AM PST//1 PM EST: Data Bootcamps
- November 10 2025 & November 24 2025 10 AM PST//1 PM EST: Office Hours
- November 14 2025: Models and Papers due
- Finalists will be announced November 21 2025
- December 5, 2025: Pitch Polish with JDRF T1D Fund
- December 12, 2025: Live Pitch
- December 15, 2025: Award
Register here by 11:59 pm PDT Sept 12 2025
Bobbi Jo Webb Roberston, PhD
Todd Brusko, PhD
Bart Roep, PhD
Kyle Gaulton, PhD
Matthias von Herrath, PhD
Linkedin: https://www.linkedin.com/in/matthias-von-herrath-b928505/
Puneet Rawat, PhD
Linkedin: https://www.linkedin.com/in/puneetrawat/
Coming Soon
Participant Requirements
- Attend a kick-off meeting for the Challenge
- Attend regular check-ins detailed in the Timeline tab over the course of the Challenge
- Utilize multiple online resources to develop a hypothesis relevant to the mechanisms, treatment or sequelae of T1D
- Manage data according to FAIR practices for sound science
- Share protocol through protocols.io
- Use online tools to provide preliminary in silico data to test hypothesis
- Present work in a written and oral form to a panel of judges
10K Prize to awarded to top team
Important Dates
Registration Deadline
September 12, 2025
Register HERE by September 12th, 2025 11:59 PM PT
Read moreD Challenge Kick-Off
September 19, 2025
Kickoff Meeting Sept 19th at 10am PT/ 1pm ET
Read more1st Bootcamp: Good Enough Practices for Reproducible Computing- Tommy Tang PhD
September 26, 2025
First Bootcamp: Friday, September 26th, 8 AM PST// 11 AM EST Good Enough Practices for Reproducible Computing – Tommy Tang PhD
Read more2nd Bootcamp: Immunological tools in mining T1D data- Puneet Rawat PhD (OSLO) and “Drug Repurposing for T1D using large scale medical knowledge graphs” – Jinfeng Zhang PhD (Insilicom)
October 3, 2025
Second Bootcamp: Friday, October 3rd, 10 AM PST// 1 PM EST Immunological tools in mining T1D data- Puneet Rawat PhD (OSLO) and “Drug Repurposing for T1D using large scale medical knowledge graphs” – Jinfeng Zhang PhD (Insilicom)
Read moreFirst Office Hours: Chen Li PhD (Texera) and Brian Corrie (PhD) (iReceptor)
October 10, 2025
First Office Hours: October 10th, 10 AM PST// 1 PM EST Chen Li PhD (Texera) and Brian Corrie (PhD) (iReceptor)
Read moreFinal Bootcamp: Mining Pankbase and Panc-DB data sets- Marcella Brissova PhD (VUMC) /Robert Faryabi PhD (PENN)
October 17, 2025
Final Bootcamp: Friday, October 17th, 10 AM PST// 1 PM EST Mining Pankbase and Panc-DB data sets – Marcella Brissova PhD (VUMC) /Robert Faryabi PhD (PENN)
Read moreSecond Office Hours – on Slack
October 24, 2025
Second Office Hours: October 24th, 10 AM PST// 1 PM EST Dr. Lin will be sharing the submission process via slack
Read moreDeadline to Submit Model and Papers
November 14, 2025
Models and Papers due: Friday November 14th, 2025 @ 11:59 PM PST
Read morePitch Polish with JDRF T1D Fund: a Breakthrough T1D venture fund
December 5, 2025
D-CHALLENGE PITCH POLISH with the JDRF T1D FUND December 5th, 2025
Read moreFrequently Asked Questions
Where can I register?
How does the challenge work? How do I use dkNET?
dkNET and the(sugar)science will provide a set of resources and a roadmap that registered individuals or teams may use to design a working hypothesis to further research in a realm of Type 1 diabetes. This data driven environment allows investigators to formulate new hypotheses around this landscape.
Use data accessed by dkNET portal, or others, to think about pathways to target to create novel hypotheses.
Attend scheduled data bootcamps (Sept 26-Oct 17 2025) to learn more.
What is our incentive to register?
Teams sign up with the incentive to earn a 10k prize to further their research, recognition from their peers and a chance to become deeply familiar with the rich array of on-line tools available to them for pursuing their research.
Can our team create several hypotheses?
Yes
When will judging be held?
Live judging is held December 12, 2025
I have a question not answered in the FAQ. Who can I contact?
Contact: monica@thesugarscience.org or neha@thesugarscience.org
What are the terms and conditions?
TERMS and Conditions of D-CHALLENGE participation:
By participating in the D-CHALLENGE, you agree to submit your team’s original work. the(sugar)science and dkNET reserve the right to share information about any winners and their work with the public. Teams may have up to 5 members. Your team will retain it’s intellectual property (“IP”) and you will decide within your team how to distribute this. Team science is a new and powerful concept and discussions by teams should occur at the start of the Challenge.
Participating in the D-CHALLENGE will result in you becoming a member on the(sugar)science and dkNET and receiving their monthly newsletters, from which you can unsubscribe at any time.
Recognizing the global nature of this competition, you expressly agree to assume any and all risks involved in or arising from your participation in this competition and release D-Challenge, dkNET and the(sugar)science as well as all its assigns, agents and competition sponsors from any liability from your participation, and agree not to sue them on account of or in connection with any claims, causes of actions, injuries, damages, costs or expenses arising from your participation in this competition.
the(sugar)science/dkNET may cancel this competition at any time if less than 10 teams register. the(sugar)science and dkNET reserve the right not to award the Prize and to suspend the competition any time if a team does not follow all written rules and regulations.
Judges from the scientific community and dkNET will determine winners of the cash prizes. These cash awards are stipulated to be used only and specifically to forward the original research discovered in the course of the D-CHALLENGE.
We reserve the right to change these Terms and Conditions by posting changes on this document. By participating in the D-CHALLENGE, you agree to be bound by any such revisions and should therefore periodically visit this page to determine the then-current Terms and Conditions to which you are bound.
Partners and Resources for 2025
dkNET
dkNET is the sponsor of the D-Challenge and provides the basis for the bioinformatics tools employed in the competition. dkNET.org is a portal created to provide information to connect the NIDDK community of researchers with scientific resources. The portal provides access to large pools of data and research resources relevant to the mission of The National Institute of Diabetes Digestive and Kidney Disease (NIDDK).
AIRR: The Adaptive Immune Receptor Repertoire
Part of the Community of the Antibody Society, a research-driven group that is organizing and coordinating stakeholders in the use of next-generation sequencing technologies to study antibody and B and T cell receptor repertoires.
- iReceptor is a science gateway tool that enables the discovery, analysis, and download of AIRR-seq data from multiple repositories: iReceptor Tool
- VDJServer is a resource for performing immune repertoire analysis and sharing data: VDJ Server
Appyters
The Gene Centric GEO Reverse Search Appyter, offers Challenge participants an opportunity to explore ways to modulate the expression of target genes based on signatures extracted from GEO studies. By querying a human or a mouse gene, this Appyter return interactive volcano plot visualization of signatures in which the given gene is maximally up- or down-regulated. A specific example, already developed for T2D, can be found in the Gene Expression T2D Signatures Appyter.
T1D TCR/ BCR genetic data repository
The T1D TCR/BCR immunological genetic database is the very first standardized and harmonized database for T1D TCR/BCR sequences.the(sugar)science together with it’s partner AIRR data commons, initiated and facilitated the build of this curated data repository.
CalR Version 1.3
protocols.io
protocols.io offers a private repository to Challenge participants with the ultimate goal of sharing work once a paper is published.
MMPC
The Mouse Metabolic Phenotyping Centers (MMPC) is a National Institutes of Diabetes and Digestive and Kidney Diseases-Sponsored resource that provides state-of-the-art technologies to investigators for a fee. Their services include characterization of mouse metabolism, blood composition (including hormones), energy balance, eating and exercise, organ function and morphology, physiology and histology.
PANCREATLAS
Pancreatlas is an online resource that houses reference imaging datasets from human pancreas samples, providing a platform for image exploration and description of pancreatic composition and architecture in health and disease.
- Human Pancreas Analysis Program (HPAP) histological (H&E) and imaging mass cytometry (IMC) images: HPAP collection
- Exeter Archival Diabetes Biobank (EADB) histological (H&E) and immunohistochemistry (IHC) images: EADB collection
- Manuscript on exocrine pancreas in type 1 diabetes, histology and fluorescent immunohistochemistry (FL IHC) images: T1D exocrine collection
TEDDY
The TEDDY study – The Environmental Determinants of Diabetes in the Young – is looking for the causes of type 1 diabetes mellitus (T1DM). T1DM used to be called childhood diabetes or insulin-dependent diabetes.
dbGaP
The database of Genotypes and Phenotypes (dbGaP) was developed to archive and distribute the data and results from studies that have investigated the interaction of genotype and phenotype in Humans.
GROUPING OF LYMPHOCYTE INTERACTIONS BY PARATOPE HOTSPOTS – GLIPH version 2
GLIPH returns significant motif lists, significant TCR convergence groups, and for each group, a collection of scores for that group indicating enrichment for motif, V-gene, CDR3 length, shared HLA among contributors, and proliferation count. When HLA data is available, it predicts the likely HLA that the set of TCRs recognizes.
TESSA
Tessa is a Bayesian model to integrate T cell receptor (TCR) sequence profiling with transcriptomes of T cells. Tessa can support TCRαβ pairing and integrate pMHC info if available. It classifies TCRs into specificity groups using machine learning.
DeepTCR
DeepTCR is a python package that has a collection of unsupervised and supervised deep learning methods to parse TCRSeq data.
TITAN
TITAN is a bimodal neural network designed to predict TCR specificity by analyzing both TCR sequences and epitopes. It can investigate T cells that are both autoreactive and/or multi-HLA restricted.
pMTnet
Deep learning neural network-based prediction of TCR’s binding specificity toward peptide-MHC complex.
NetTCR
Enables accurate prediction of TCR-peptide binding by using paired TCRα and β sequence data.
IGoR
A tool for high-throughput immune repertoire analysis. Can simulates naive TCR repertoires based on generative probabilities
Immunomap
Deep learning neural network-based prediction of TCR’s binding specificity toward peptide-MHC complex.
T1D Knowledge Portal is a new way to access T1D
T1D Knowledge Portal enables browsing, searching, and analysis of human genetic information linked to type 1 diabetes and related traits, while protecting the integrity and confidentiality of the underlying data.
IIDP Research Data Repository
The Integrated Islet Distribution Program (IIDP), founded in 2010, offers an extensive donor and islet characteristics database to approved researchers through the IIDP’s Research Data Repository (RDR). The graphs below summarize several key datapoints, and the “Available Datapoints” tree shows data fields accessible to approved IIDP researchers.
The Human Genetics Amplifier (HuGeAMP)
A software platform and infrastructure that aggregates, integrates, and analyzes human genetic and genomic data to spark insights into complex diseases, including Common Metabolic Diseases Knowledge Portal (KP) , Type 1 Diabetes KP, Type 2 Diabetes KP, Kidney Disease KP, Sleep Disease KP, Cardiovascular Disease KP, Cerebrovascular Disease KP, Adipose Tissue Knowledge Portal, …etc.
Common Metabolic Diseases Knowledge Portal (CMDKP)
The Common Metabolic Diseases Knowledge Portal aggregates, analyzes, and displays human genetic and functional genomic information linked to common metabolic diseases and traits, while protecting the integrity and confidentiality of the underlying data.
Type 2 Diabetes Knowledge Portal (T2DKP)
The T2D Knowledge Portal enables browsing, searching, and analysis of human genetic information linked to type 2 diabetes and related traits, while protecting the integrity and confidentiality of the underlying data.
Adipose Tissue Knowledge Portal
The adipose tissue knowledge portal provides open-access to clinical, transcriptional and protein data down to the single-cell level.
NIDDK Central Repository
(Data not available immediately)
NIDDK Central Repository – Resources for Research (NIDDK-CR R4R) facilitates sharing of data, specimens, and other resources generated from studies supported by NIDDK and within NIDDK’s mission by making these resources available for request to the broader scientific and research community.
PANC-DB
PANC-DB is the open-source data repository, dissemination and visualization vehicle for the cellular and molecular datasets generated by the Human Pancreas Analysis Program (HPAP), making genomic and islet function data highly accessible to the broader diabetes research community.
Diabetes Data and Hypothesis Hub (D2H2)
A platform that facilitates data-driven hypothesis generation for the diabetes and related metabolic disorder research community
Secrepedia.org
An encyclopedia of the white and brown adipocyte secretome in mouse models and humans
A single cell atlas of human and mouse white adipose tissue
A detailed cellular atlases of human and murine subcutaneous and visceral white fat at single cell resolution across a range of body weight. The data comprise an extensive resource for the exploration of genes, traits, and cell types in the function of WAT across species, depots, and nutritional conditions.
Bridge2AI AI-READI (Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights)
AI-READI project seeks to create a flagship ethically-sourced dataset to enable future generations of artificial intelligence/machine learning (AI/ML) research to provide critical insights into type 2 diabetes mellitus (T2DM), including salutogenic pathways to return to health.
TOPMed (Trans-Omics for Precision Medicine)
TOPMed, a program of the NHLBI, aims to improve scientific understanding of the fundamental biological processes that underlie heart, lung, blood, and sleep (HLBS) disorders and advance precision medicine in ways that lead to disease treatments tailored to individuals’ unique genes and environments.
All of US
The All of Us Research Hub stores health data from a diverse group of participants from across the United States
MoTrPAC (Molecular Transducers of Physical Activity Consortium)
MoTrPAC develops the compendium of molecular transducers (the ‘molecular map’) that respond to acute and chronic exercise.
Human Cell Atlas (HCA)
HCA community is profiling millions of human cells, a process that generates enormous amounts of data that scientists need to store, standardize and interpret.
Metabolomics Workbench
Resources that are available to the research community in finding, accessing, and using the metabolomics data and its integration with other omics data.
HumanIslets.com (CANADA)
An open resource currently includes data on 547 human islet donors, offering researchers access to linked datasets describing molecular omics profiles, islet functions, and donor phenotypes, and enabling statistical, visual, and functional analyses at donor, islet, or single-cell levels while considering potential confounders.
Collaborative Microbial Metabolite Center (CMMC)
A knowledgebase to ensure it can be reused to make it easier to mechanistically understand the functional role of the microbiome, accomplished through digitizing the relationships between diet, host and microbial metabolism and the activities of the metabolites.
NetTCR
Enables accurate prediction of TCR-peptide binding by using paired TCRα and β sequence data.
Arc Institute
Useful Resources listed under dkNET webinars
Resources suggested by NIDDK program staff and examples to show you how to use them to apply to diabetes research
Arc Virtual Cell Atlas
The Arc Virtual Cell Atlas is a collection of high quality, curated, open datasets assembled for the purpose of accelerating the creation of virtual cell models. The Atlas includes both observational and perturbational data from over 300 million cells (and growing).
JAEB
Ongoing studies and datasets provided through the Jaeb Center for Health Research who focus on projects involving eye disorders or type 1 diabetes
TERMS and Conditions of D-CHALLENGE participation:
By participating in the D-CHALLENGE, you agree to submit your team’s original work. the(sugar)science and dkNET reserve the right to share information about any winners and their work with the public. Teams may have up to 5 members. Your team will retain it’s intellectual property (“IP”) and you will decide within your team how to distribute this. Team science is a new and powerful concept and discussions by teams should occur at the start of the Challenge.
Participating in the D-CHALLENGE will result in you becoming a member on the(sugar)science and dkNET and receiving their monthly newsletters, from which you can unsubscribe at any time.
Recognizing the global nature of this competition, you expressly agree to assume any and all risks involved in or arising from your participation in this competition and release D-Challenge, dkNET and the(sugar)science as well as all its assigns, agents and competition sponsors from any liability from your participation, and agree not to sue them on account of or in connection with any claims, causes of actions, injuries, damages, costs or expenses arising from your participation in this competition.
the(sugar)science/dkNET may cancel this competition at any time if less than 10 teams register. the(sugar)science and dkNET reserve the right not to award the Prize and to suspend the competition any time if a team does not follow all written rules and regulations.
Judges from the scientific community and dkNET will determine winners of the cash prizes. These cash awards are stipulated to be used only and specifically to forward the original research discovered in the course of the D-CHALLENGE.
We reserve the right to change these Terms and Conditions by posting changes on this document. By participating in the D-CHALLENGE, you agree to be bound by any such revisions and should therefore periodically visit this page to determine the then-current Terms and Conditions to which you are bound.