Update _viash.yaml (#4)

Author: lazappi

_viash.yaml

@@ -1,78 +1,50 @@
 viash_version: 0.9.0
 
-# Step 1: Change the name of the task.
-# example: task_name_of_this_task
 name: task_foundation_models
 organization: openproblems-bio
 version: dev
 
 license: MIT
-# Step 2: Add keywords to describe the task.
-keywords: [single-cell, openproblems, benchmark]
-# Step 3: Update the `task_template` to the name of the task from step 1.
+keywords: [single-cell, openproblems, benchmark, "foundation models"]
 links:
   issue_tracker: https://github.com/openproblems-bio/task_foundation_models/issues
   repository: https://github.com/openproblems-bio/task_foundation_models
   docker_registry: ghcr.io
 
-
-# Step 4: Update the label, summary and description.
-# A unique, human-readable, short label. Used for creating summary tables and visualisations.
-label: Template
-summary: A one sentence summary of purpose and methodology. Used for creating an overview tables.
+label: Foundation models
+summary: Modeling of single-cells to perform multiple tasks using foundation models
 description: |
-  Provide a clear and concise description of your task, detailing the specific problem it aims
-  to solve. Outline the input data types, the expected output, and any assumptions or constraints.
-  Be sure to explain any terminology or concepts that are essential for understanding the task.
+  Recent developments in deep-learning have led to the creation of several 'foundation models' for single-cell data.
+  These are large models that have been trained on data from millions of cells and am to fully capture the variability in the single-cell landscape.
+  Typically, they use a transformer architecture [@szalata2024transformers] and undergo self-supervised pre-training using masking of parts of the input data.
+  Trained foundation models can then be applied to a variety of downstream tasks, either by directly feeding new data into the model or by fine-tuning to better fit a new dataset or to produce a specific output.
+  The general nature of single-cell foundation models and the large amount of data they have been trained on makes them potentially powerful tools for single-cell analysis but their performance is yet to be fully established.
 
-  Explain the motivation behind your proposed task. Describe the biological or computational 
-  problem you aim to address and why it's important. Discuss the current state of research in
-  this area and any gaps or challenges that your task could help address. This section 
-  should convince readers of the significance and relevance of your task.
+  Open Problems builds on existing evaluations [@boiarsky2023foundationmodels; @liu2024foundationmodels] of foundation models by incorporating them into our continuous benchmarking framework.
 
-# A list of references to relevant literature. Each reference should be a DOI or a bibtex entry
 references:
   doi:
-    - 10.21203/rs.3.rs-4181617/v1
-  # bibtex:
-  #   - |
-  #     @article{doe_2021_template,
-  #       doi = {10.21203/rs.3.rs-4181617/v1},
-  #       url = {https://doi.org/10.21203/rs.3.rs-4181617/v1},
-  #       author = {Doe, John},
-  #       title = {A template for creating new tasks},
-  #       publisher = {Research Square},
-  #       year = {2021},
-  #     }
-  
+    - 10.1101/2023.10.19.563100
+    - 10.1101/2023.09.08.555192
+
 info:
-  image: The name of the image file to use for the component on the website.
-  # Step 5: Replace the task_template to the name of the task.
+  image: thumbnail.svg
   test_resources:
     - type: s3
       path: s3://openproblems-data/resources_test/task_foundation_models/
       dest: resources_test/task_foundation_models
 
-# Step 6: Update the authors of the task.
-authors: 
-  # Full name of the author, usually in the name of FirstName MiddleName LastName.
-  - name: John Doe
-    # Role of the author. Possible values:
-    # 
-    # * `"author"`: Authors who have made substantial contributions to the component.
-    # * `"maintainer"`: The maintainer of the component.
-    # * `"contributor"`: Authors who have made smaller contributions (such as code patches etc.).
-    roles: [ "author", "maintainer" ]
-    # Additional information on the author
-    info: 
-      github: johndoe
-      orcid: 0000-0000-0000-0000
-      email: john@doe.me
-      twitter: johndoe
-      linkedin: johndoe
-
-# Step 7: Remove all of the comments of the steps you completed
-# Step 8: High five yourself!
+authors:
+  - name: Robrecht Cannoodt
+    roles: [author, maintainer]
+    info:
+      github: rcannood
+      orcid: "0000-0003-3641-729X"
+  - name: Luke Zappia
+    roles: [author]
+    info:
+      github: lazappi
+      orcid: 0000-0001-7744-8565
 
 config_mods: |
   .runners[.type == "nextflow"].config.labels := { lowmem : "memory = 20.Gb", midmem : "memory = 50.Gb", highmem : "memory = 100.Gb", lowcpu : "cpus = 5", midcpu : "cpus = 15", highcpu : "cpus = 30", lowtime : "time = 1.h", midtime : "time = 4.h", hightime : "time = 8.h", veryhightime : "time = 24.h" }