CENTURI Hackathon
2024

CENTURI Hackathon
2024

For quantitative biology

Centre de séminaires

Villages Clubs du Soleil, Belle de Mai, Marseille

What is the CENTURI Hackathon?

The CENTURI Hackathon is a fast-paced two-day event of coding, engineering and idea-sharing to drive innovations at the interface of Computer Science and  Life Sciences. The event is aimed at curious and creative minds interested in improving their coding skills through collaborative projects. The event is open to students, postdocs, developers and researchers.

The goal of our Hackathon is to computationally unlock technological bottlenecks arising from the study of Living Systems. Our event is aimed at everyone with experience in coding and with a keen interest in problem solving in big data, computer vision or modeling. Experts in fields such as biology, mathematics and non-scientific developers are encouraged to apply!

Curious about the previous editions? Find out more about the 2022 Hackathon, the 2023 Hackathon and the 2023 Hackathon projects here!

 

Hackaton-Affiche-2024-final

What types of projects will participants be working on ?

Projects will strive to solve key technological bottlenecks in a variety of topics, such as Computer vision, Modeling, Data mining and Computer assisted microscopy.

 

Participants will work on big data projects for living systems, with projects from academic labs in CENTURI and elsewhere.

CENTURI Hackathon will welcome a maximum of 60 participants. Applicants should have some experience with coding.

Participants will work in groups of 6-8 people on various projects  in a variety of topics:

  • Data visualization and interactions
  • Computer vision
  • Data mining
  • Robotics & Computer assisted microscopy
  • Modelling

Projects are as follows:

EmbryoFlowTracker | Léo Guignard

 

Keywords: Embryo Development, Tracking Algorithms, Vector Flow

Understanding the formation of life from a single fertilised cell requires a detailed description of this process. Many researchers have focused on deciphering cell dynamics, studying how cells organised into tissues, organs, and eventually an entire organism.

Considerable progress has been made in quantifying cell movement within whole embryos. This progress began with advancements in microscope technologies, such as light-sheet microscopy, allowing researchers to observe all the cells in an embryo over extended periods.

Parhyale

However, extracting quantitative data from these complex datasets required the development of specialised computational tools. Despite advancements, challenges remain in automating cell identification and tracking within 3D movies. In this project, the team will work with large 3D+time datasets to improve tracking algorithms using precise non-linear vector fields.

To support algorithm development, the team will have access to resources including 500 time points of a 3D movie showing the development of a Parhyale embryo, loose segmentation data for each time point, and non-linear vector fields linking consecutive time points. Additionally, to validate their method, they will have manual partial cell detection and tracking data for over 400 time points.

This interdisciplinary effort aims to shed light on the intricate processes of cell behaviour during embryo development, using advanced technology and analytical approaches.

Technical and Technological Bottlenecks: The main technical bottleneck lies in developing efficient algorithms to accurately track cells using non-linear vector fields. Current approaches lack the precision required for this task.

Programming Language & Toolbox: The algorithm will be implemented in Python, leveraging libraries such as NumPy, SciPy, and scikit-learn for data processing and machine learning. Visualisation will be handled with Matplotlib and Plotly.

Expected Deliverable / Output: The team aims to deliver "EmbryoFlowTracker," a software tool for precise cell tracking in developing embryos using non-linear vector fields. This tool will provide researchers with a user-friendly interface to analyse 3D+time datasets of embryo development. Additionally, the project will produce a research paper detailing the algorithm's performance and its application to the provided Parhyale embryo dataset

Figure 1. (left) Single-molecule force spectroscopy data are obtained by pulling on a single protein. The force exerted on the molecule increases as it is pulled, and is drops when a domain unfolds. Each peak on the force-distance curve therefore corresponds to an unfolding or a break. (middle) Not all the force curves show interesting events, so large dataset are acquired. (right) The data are quite noisy and detection of the unfolding peaks (highlighted in red) is challenging automatically.
Figure 1. (left) Single-molecule force spectroscopy data are obtained by pulling on a single protein. The force exerted on the molecule increases as it is pulled, and is drops when a domain unfolds. Each peak on the force-distance curve therefore corresponds to an unfolding or a break. (middle) Not all the force curves show interesting events, so large dataset are acquired. (right) The data are quite noisy and detection of the unfolding peaks (highlighted in red) is challenging automatically.

DeepForce: Deep single molecule unfolding detection | Felix Rico, Claire Valotteau, Ismahene Mesbah

 

Receptor-ligand bonds are a central part of any biological process and protein folding is one of the unsolved problems in biology. These two processes can be probed at the single molecule level using force spectroscopy experiments. Single Molecule Force Spectroscopy is based on the acquisition of force-distance curves in which a single molecule, e.g. a protein, is pulled and force required to unfold or unbind it is measured.

Experimentally, only about 10% of these curves show an interesting signature (unbinding and/or unfolding peak), the others show no event.  An example of the output is given in the figure below. The automatic detection of those noisy and heterogeneous events is very challenging and requires specific tools for an accurate and trustworthy analysis of molecular mechanics.

For this hackathon, we will develop sensitive deep-learning methods to pre-select the curves with interesting events, and then to classify the events and extract the molecular forces. We envision the following milestones to carry out this project.

  1. Training a recurrent neural network on simple simulation
  2. Experiment with real annotated data
  3. Development of a simple GUI for results exploration and re-training

Programming language & Toolbox Python, Matlab...

Dataset: Thousands of force curves from atomic force microscopy measurements of single molecule unfolding. Simulated force curves mimicking AFM experimental results.

EndoTrack: visualizing the movements of intracellular organelles in developing tissues | Claudio Collinet

 

Keywords: Morphogenesis, Visualization, Cell Dynamics, Multiple object tracking.

Morphogenesis is the emergence of new shapes in tissues and organisms during their embryonic development. Understanding this process is crucial to studying its disruption in embryonic malformations or tumor formation. Imaging experiments on embryos, such as those of the fruitfly Drosophila, uncovered that cells move, intercalate and change geometry to drive morphogenesis.

Asset 3

These processes are driven by fundamental intracellular processes, such as endocytic trafficking, where the collective dynamics of hundreds of intracellular organelles allow the redistribution of membrane molecules within the cell. Despite progress in 3D live imaging, the exact role of the endocytic process is poorly understood due to the complexity of the volumetric sequence. Indeed, visualization and interpretation are challenged by the multifactorial origins of motions (coming from cellular displacement, membrane reorganization and endocytosis itself) as well as its stochastic nature.

In this context, the goal of this project is the development of a toolset to change the ways we look at volumetric sequences. Instead of manually navigating a complex dataset, the user will be able to select a cell of interest to automatically visualize a dynamic 3D ROIs that follow the cell as they move through the sample. In those new movies devoid of cellular motion, the delicate orchestration of endocytic events will be now observable and even quantifiable. We have identified the following milestone toward this goal:

  1. Automatizing the tracking of cell on the epithelium in 2D first using membrane markers (Gap43 or Dextran) using off-the-shelf 2D segmentation tools (e.g. https://github.com/baigouy/EPySeg), tracking approach (e.g. https://github.com/DanuserLab/u-track) and 2D annotation for validation.
  2. Porting this implementation to 3D using the 2D pre-segmentation and motion as a starting point. Endocytic trackability  (https://github.com/DanuserLab/u-track3D) could be used to evaluate the results.
  3. Build a dynamic ROI program that follows a single tracked cell and provides a static view.

Datasets: 3D time lapse images of Drosophila embryo acquired at IBDM by Claudio Collinet.

Programming Language & Toolbox: Python and optionally matlab

Useful Information

The event will take place from June 28 to June 30, 2024 at the Centre de séminaires Villages Clubs du Soleil, Belle de Mai, Marseille.

CENTURI Hackathon will welcome a maximum of 60 participants. Applicants should have some experience with coding.

Each participant should bring a laptop.

CENTURI will provide meals during the event (buffet) from June 28 to June 30.

CENTURI will cover accommodation and catering. CENTURI will not cover transportation nor additional costs.

In case of financial difficulties for transportation, you may contact us at info@centuri-livingsystems.org.

Registration is free for all participants.

However, registered participants are expected to participate in the entire event (from June 28 early evening to June 30 early evening). After registering to the Hackathon, you will be contacted early May to select your projects.

For informal enquiries: info@centuri-livingsystems.org

Format

The CENTURI Hackathon will start on Friday, June 28, in the evening and will end on Sunday, June 30, at the end of the afternoon.

Deadline

Deadline for application: June 7, 2024

Venue

CENTURI Hackathon will take place in the Centre de séminaires  Villages Clubs du Soleil, Belle de Mai, Marseille. 

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