adding participants

participants/adapts.md

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+---
+title: Precision Nutrition research group at  University of Sydney
+description: The project aims to model temporal tumour adaptations to therapy and predict targetable vulnerabilities, based on non-invasive blood profiling, for therapeutic adjustments of patients with DMG under treatment.
+toc: false
+type: ABLeS Participant
+---
+
+## Project title
+
+Development of the ADvanced mAchine learning Precision Treatment Strategy (ADAPTS) platform for patients with Diffuse Midline Glioma (DMG)
+
+## Collaborators and funding
+
+**Funding partners:** The Kids’ Cancer Project, RUN DIPG
+
+**Collaborators:**
+
+- Dieter Henrik Heiland, The MILO laboratory, University of Freiburg, Germany
+
+- Nada Jabado, [Nada Jabado Laboratory](https://www.jabadolab.com/), [McGill institute](https://www.mcgill.ca/fr), Montréal, Canada
+
+- Sebastian Waszak, [Waszak Lab](https://www.epfl.ch/labs/upwaszak/), [École Polytechnique Fédérale de Lausanne](https://www.epfl.ch/fr/), Switerzland
+
+- Sabine Mueller, University of California San Fransisco, United States
+
+- Nick Vitanza, Vitanza Lab, Seattle Children’s Research Institute, United States
+
+- Rob Salomon, University of New South Wales, Sydney, Australia
+
+- Santosh Valvi, [The University of Western Australia](https://www.uwa.edu.au/), Australia
+
+**Bioinformatics support:**
+
+- Australian BioCommons
+
+- Mark Cowley, [Children’s Cancer Institute](https://www.ccia.org.au/),  Sydney, Australia.
+
+- Digital Technology Solutions, Australia
+
+
+## Contact(s)
+
+- **Project lead:** Matthew D. Dun, University of Newcastle, Australia, <[email protected]>
+
+- **Project co-lead:** Fatima Valdes Mora, University of New South Wales, Sydney, <[email protected]>
+
+- **Bioinformatics lead:** Tuan Vo, University of Newcastle, Australia, <[email protected]>
+
+
+## Project description and aims
+
+Diffuse midline glioma (DMG) is a uniformly fatal brain tumour, representing the most common cause of cancer-related death in children. Despite extensive research efforts, radiotherapy remains the sole treatment option and patients still tragically succumb within a year of diagnosis. It remains clear that in the clinical setting, our current armamentarium against DMG falls desperately short of acceptable, highlighting the urgent imperative for innovative research and therapeutic strategies.
+
+This project aims to develop the ADvanced mAchine learning Precision Treatment Strategy (ADAPTS) platform, which will enable the analysis of time-series multiomics data from core biopsies, cerebrospinal fluid, and peripheral blood samples collected from both on-treatment patients and DMG mouse models. This framework will enable to model tumour adaptation to treatments and identify the next targetable vulnerability. To achieve this, machine learning models are trained on on-treatment matched tumour and blood samples to help predicting the relevant timeframe for administering the subsequent treatment based on blood profiling. The objective of this project aligns with the era of personalised medicine, as we aim to adjust therapeutic regimens throughout the treatment journey of patients using non-invasive techniques to enhance their survival and quality of life.
+
+
+## How is ABLeS supporting this work?
+
+This work is supported through Production bioinformatics scheme provided by ABLeS. The supports includes unlimited temporary storage on scratch, 15 TB permenant storage, 35 TB temporary stroage and 50 KSUs per quarter.
+
+## Expected outputs enabled by participation in ABLeS
+
+A public ADAPTS platform, featuring computational workflows developed on GitHub, and freely accessible datasets available for researchers and clinicians to analyse the temporal adaptation of therapeutics used in DMG treatment. The machine learning models trained on these data are anticipated to inform the clinical management of DMG patients by suggesting a temporal and sequential treatment plan tailored to each patient's tumour biology in real-time using non-invasive blood profiling. Our goal is to publish our findings in high-impact journals such as Cancer Cell.
+
+
+<br/>
+
+> *These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above.*

participants/woodcroft-grp.md

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+---
+title:  Woodcroft group, Centre for Microbiome Research, Queensland University of Technology
+description: Recovering reference microbial genomes from public metagenomes. We hope to recover taxonomically novel genomes, using Bin Chicken to decide which public metagenomes to analyse together.
+toc: false
+type: ABLeS Participant
+---
+
+## Project title
+
+Recovery of novel microbial genomes with Bin Chicken
+
+## Collaborators and funding
+
+- [Woodcroft group](https://research.qut.edu.au/cmr/team/ben-woodcroft/), Centre for Microbiome Research, Queensland University of Technology
+
+- [EMERGE Biology Integration Institute](https://emerge-bii.github.io/), National Science Foundation, United States
+
+
+## Contact(s)
+
+- Samuel Aroney, QUT, <[email protected]>
+
+- Ben Woodcroft, QUT, <[email protected]>
+
+- Yibi Chen, QUT, <[email protected]> 
+
+## Project description and aims
+
+Despite large-scale genome recovery efforts, most microbial species lack a reference genome. We aim to produce novel microbial reference genomes from public metagenomes via new techniques. To this end we have created [Bin Chicken](https://github.com/AroneyS/binchicken/), a tool that predicts the best samples to combine for coassembly, allowing recovery of novel genomes. 
+
+## How is ABLeS supporting this work?
+
+This work is supported through the reference data generation scheme provided by ABLeS. The supports includes 5 TB long term storage and 100 KSUs per quarter.
+
+## Expected outputs enabled by participation in ABLeS
+
+Microbial genomes linked to SRA metadata will be made available on a public database such as NCBI.
+Biogeography of newly recovered species will be published in a research article and on the [Sandpiper](https://sandpiper.qut.edu.au/) website.
+Publication of results (both direct and downstream) in academic journals.
+In each case, the ABLeS scheme will be acknowledged.
+
+
+<br/>
+
+> *These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above.*