diff --git a/_viash.yaml b/_viash.yaml
index 4c0572bb..1df7d655 100644
--- a/_viash.yaml
+++ b/_viash.yaml
@@ -1,9 +1,51 @@
 name: task_perturbation_prediction
-version: 1.1.0
-
-# package metadata
+label: Perturbation Prediction
+summary: Predicting how small molecules change gene expression in different cell types.
 description: |
-  Predicting how small molecules change gene expression in different cell types.
+  Human biology can be complex, in part due to the function and interplay of the body's
+  approximately 37 trillion cells, which are organized into tissues, organs, and systems.
+  However, recent advances in single-cell technologies have provided unparalleled insight
+  into the function of cells and tissues at the level of DNA, RNA, and proteins. Yet
+  leveraging single-cell methods to develop medicines requires mapping causal links
+  between chemical perturbations and the downstream impact on cell state. These experiments
+  are costly and labor intensive, and not all cells and tissues are amenable to
+  high-throughput transcriptomic screening. If data science could help accurately predict
+  chemical perturbations in new cell types, it could accelerate and expand the development
+  of new medicines.
+
+  Several methods have been developed for drug perturbation prediction, most of which are
+  variations on the autoencoder architecture (Dr.VAE, scGEN, and ChemCPA). However, these
+  methods lack proper benchmarking datasets with diverse cell types to determine how well
+  they generalize. The largest available training dataset is the NIH-funded Connectivity
+  Map (CMap), which comprises over 1.3M small molecule perturbation measurements. However,
+  the CMap includes observations of only 978 genes, less than 5% of all genes. Furthermore,
+  the CMap data is comprised almost entirely of measurements in cancer cell lines, which
+  may not accurately represent human biology.
+
+  This task aims to predict how small molecules change gene expression in different cell
+  types. This task was a [Kaggle competition](https://www.kaggle.com/competitions/open-problems-single-cell-perturbations/overview)
+  as part of the [NeurIPS 2023 competition track](https://neurips.cc/virtual/2023/competition/66586).
+
+  The task is to predict the gene expression profile of a cell after a small molecule
+  perturbation. For this competition, we designed and generated a novel single-cell
+  perturbational dataset in human peripheral blood mononuclear cells (PBMCs). We
+  selected 144 compounds from the Library of Integrated Network-Based Cellular Signatures
+  (LINCS) Connectivity Map dataset ([PMID: 29195078](https://pubmed.ncbi.nlm.nih.gov/29195078/))
+  and measured single-cell gene
+  expression profiles after 24 hours of treatment. The experiment was repeated in three
+  healthy human donors, and the compounds were selected based on diverse transcriptional
+  signatures observed in CD34+ hematopoietic stem cells (data not released). We performed
+  this experiment in human PBMCs because the cells are commercially available with
+  pre-obtained consent for public release and PBMCs are a primary, disease-relevant tissue
+  that contains multiple mature cell types (including T-cells, B-cells, myeloid cells,
+  and NK cells) with established markers for annotation of cell types. To supplement this
+  dataset, we also measured cells from each donor at baseline with joint scRNA and
+  single-cell chromatin accessibility measurements using the 10x Multiome assay. We hope
+  that the addition of rich multi-omic data for each donor and cell type at baseline will
+  help establish biological priors that explain the susceptibility of particular genes to
+  exhibit perturbation responses in difference biological contexts.
+
+version: dev
 license: MIT
 keywords: [single-cell, perturbation prediction, perturbation, openproblems, benchmark]
 links:
@@ -11,6 +53,59 @@ links:
   repository: https://github.com/openproblems-bio/task_perturbation_prediction
   docker_registry: ghcr.io
 
+authors:
+  - name: Artur Szałata
+    roles: [ author ]
+    info:
+      github: szalata
+      orcid: "000-0001-8413-234X"
+  - name: Robrecht Cannoodt
+    roles: [ author ]
+    info:
+      github: rcannood
+      orcid: "0000-0003-3641-729X"
+  - name: Daniel Burkhardt
+    roles: [ author ]
+    info:
+      github: dburkhardt
+      orcid: 0000-0001-7744-1363
+  - name: Malte D. Luecken
+    roles: [ author ]
+    info:
+      github: LuckyMD
+      orcid: 0000-0001-7464-7921
+  - name: Tin M. Tunjic
+    roles: [ contributor ]
+    info:
+      github: ttunja
+      orcid: 0000-0001-8842-6548
+  - name: Mengbo Wang
+    roles: [ contributor ]
+    info:
+      github: wangmengbo
+      orcid: 0000-0002-0266-9993
+  - name: Andrew Benz
+    roles: [ author ]
+    info:
+      github: andrew-benz
+      orcid: 0009-0002-8118-1861
+  - name: Tianyu Liu
+    roles: [ contributor ]
+    info:
+      github: HelloWorldLTY
+      orcid: 0000-0002-9412-6573
+  - name: Jalil Nourisa
+    roles: [ contributor ]
+    info:
+      github: janursa
+      orcid: 0000-0002-7539-4396
+  - name: Rico Meinl
+    roles: [ contributor ]
+    info:
+      github: ricomnl
+      orcid: 0000-0003-4356-6058
+
+
 # technical settings
 organization: openproblems-bio
 viash_version: 0.9.0
@@ -22,4 +117,4 @@ info:
 
 # set default labels
 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" }
\ No newline at end of file
+  .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" }
diff --git a/src/api/file_de_test.yaml b/src/api/file_de_test.yaml
index d31e047f..33d2b615 100644
--- a/src/api/file_de_test.yaml
+++ b/src/api/file_de_test.yaml
@@ -1,10 +1,10 @@
 type: file
 example: resources/datasets/neurips-2023-data/de_test.h5ad
+label: DE test
+summary: "Differential expression results for testing."
 info:
-  label: DE test
-  summary: "Differential expression results for testing."
-  file_type: h5ad
-  slots:
+  format:
+    type: h5ad
     obs:
       - name: cell_type
         type: string
diff --git a/src/api/file_de_train.yaml b/src/api/file_de_train.yaml
index a7ff239b..cb5636b6 100644
--- a/src/api/file_de_train.yaml
+++ b/src/api/file_de_train.yaml
@@ -1,10 +1,10 @@
 type: file
 example: resources/datasets/neurips-2023-data/de_train.h5ad
+label: DE train
+summary: "Differential expression results for training."
 info:
-  label: DE train
-  summary: "Differential expression results for training."
-  file_type: h5ad
-  slots:
+  format:
+    type: h5ad
     obs:
       - name: cell_type
         type: string
diff --git a/src/api/file_id_map.yaml b/src/api/file_id_map.yaml
index a1551abe..63a8310b 100644
--- a/src/api/file_id_map.yaml
+++ b/src/api/file_id_map.yaml
@@ -1,19 +1,20 @@
 type: file
 example: resources/datasets/neurips-2023-data/id_map.csv
+label: ID Map
+summary: "File indicates the order of de_test, the cell types and the small molecule names."
 info:
-  label: ID Map
-  summary: "File indicates the order of de_test, the cell types and the small molecule names."
-  file_type: csv
-  columns:
-    - name: id
-      type: integer
-      description: Index of the test observation
-      required: true
-    - name: cell_type
-      type: string
-      description: "Cell type name"
-      required: true
-    - name: sm_name
-      type: string
-      description: "Small molecule name"
-      required: true
+  format:
+    type: csv
+    columns:
+      - name: id
+        type: integer
+        description: Index of the test observation
+        required: true
+      - name: cell_type
+        type: string
+        description: "Cell type name"
+        required: true
+      - name: sm_name
+        type: string
+        description: "Small molecule name"
+        required: true
diff --git a/src/api/file_model.yaml b/src/api/file_model.yaml
index b7e9a988..d4c47277 100644
--- a/src/api/file_model.yaml
+++ b/src/api/file_model.yaml
@@ -1,6 +1,4 @@
 type: file
 example: resources/datasets/neurips-2023-data/model/
-info:
-  label: Model
-  summary: "Optional model output. If no value is passed, the model will be removed at the end of the run."
-  file_type: directory
\ No newline at end of file
+label: Model
+summary: "Optional model output. If no value is passed, the model will be removed at the end of the run."
diff --git a/src/api/file_prediction.yaml b/src/api/file_prediction.yaml
index 80b279b6..eda23ceb 100644
--- a/src/api/file_prediction.yaml
+++ b/src/api/file_prediction.yaml
@@ -1,10 +1,10 @@
 type: file
 example: resources/datasets/neurips-2023-data/prediction.h5ad
+label: Prediction
+summary: "Differential Gene Expression prediction"
 info:
-  label: Prediction
-  summary: "Differential Gene Expression prediction"
-  file_type: h5ad
-  slots:
+  format:
+    type: h5ad
     layers:
       - name: prediction
         type: double
diff --git a/src/api/file_sc_counts.yaml b/src/api/file_sc_counts.yaml
index 493cc6a2..a760f008 100644
--- a/src/api/file_sc_counts.yaml
+++ b/src/api/file_sc_counts.yaml
@@ -1,10 +1,10 @@
 type: file
 example: resources/neurips-2023-raw/sc_counts.h5ad
+label: Single Cell Counts
+summary: "Anndata with the counts of the whole dataset."
 info:
-  label: Single Cell Counts
-  summary: "Anndata with the counts of the whole dataset."
-  file_type: h5ad
-  slots:
+  format:
+    type: h5ad
     obs:
       - name: dose_uM
         description: "Dose in micromolar."
diff --git a/src/api/file_score.yaml b/src/api/file_score.yaml
index 3ec5c36a..258aa689 100644
--- a/src/api/file_score.yaml
+++ b/src/api/file_score.yaml
@@ -1,10 +1,10 @@
 type: file
 example: resources/datasets/neurips-2023-data/score.h5ad
+label: Score
+summary: "File indicating the score of a metric."
 info:
-  label: Score
-  summary: "File indicating the score of a metric."
-  file_type: h5ad
-  slots:
+  format:
+    type: h5ad
     uns:
       - type: string
         name: dataset_id
diff --git a/src/api/task_info.yaml b/src/api/task_info.yaml
deleted file mode 100644
index c0dfb93f..00000000
--- a/src/api/task_info.yaml
+++ /dev/null
@@ -1,141 +0,0 @@
-name: perturbation_prediction
-label: Perturbation Prediction
-summary: Predicting how small molecules change gene expression in different cell types.
-readme: |
-  ## Installation
-
-  You need to have Docker, Java, and Viash installed. Follow
-  [these instructions](https://openproblems.bio/documentation/fundamentals/requirements)
-  to install the required dependencies.
-
-  ## Add a method
-
-  To add a method to the repository, follow the instructions in the `scripts/add_a_method.sh` script.
-
-  ## Frequently used commands
-  
-  To get started, you can run the following commands:
-
-  ```bash
-  git clone git@github.com:openproblems-bio/task_perturbation_prediction.git
-
-  cd task_perturbation_prediction
-  
-  # download resources
-  scripts/download_resources.sh
-  ```
-
-  To run the benchmark, you first need to build the components. Afterwards, you can run the benchmark:
-  
-  ```bash
-  viash ns build --parallel --setup cachedbuild
-
-  scripts/run_benchmark.sh
-  ```
-
-  After adding a component, it is recommended to run the tests to ensure that the component is working correctly:
-
-  ```bash
-  viash ns test --parallel
-  ```
-  
-  Optionally, you can provide the `--query` argument to test only a subset of components:
-
-  ```bash
-  viash ns test --parallel --query "component_name"
-  ```
-motivation: |
-  Human biology can be complex, in part due to the function and interplay of the body's
-  approximately 37 trillion cells, which are organized into tissues, organs, and systems.
-  However, recent advances in single-cell technologies have provided unparalleled insight
-  into the function of cells and tissues at the level of DNA, RNA, and proteins. Yet
-  leveraging single-cell methods to develop medicines requires mapping causal links
-  between chemical perturbations and the downstream impact on cell state. These experiments
-  are costly and labor intensive, and not all cells and tissues are amenable to
-  high-throughput transcriptomic screening. If data science could help accurately predict
-  chemical perturbations in new cell types, it could accelerate and expand the development
-  of new medicines.
-
-  Several methods have been developed for drug perturbation prediction, most of which are
-  variations on the autoencoder architecture (Dr.VAE, scGEN, and ChemCPA). However, these
-  methods lack proper benchmarking datasets with diverse cell types to determine how well
-  they generalize. The largest available training dataset is the NIH-funded Connectivity
-  Map (CMap), which comprises over 1.3M small molecule perturbation measurements. However,
-  the CMap includes observations of only 978 genes, less than 5% of all genes. Furthermore,
-  the CMap data is comprised almost entirely of measurements in cancer cell lines, which
-  may not accurately represent human biology.
-description: |
-  This task aims to predict how small molecules change gene expression in different cell
-  types. This task was a [Kaggle competition](https://www.kaggle.com/competitions/open-problems-single-cell-perturbations/overview)
-  as part of the [NeurIPS 2023 competition track](https://neurips.cc/virtual/2023/competition/66586).
-
-  The task is to predict the gene expression profile of a cell after a small molecule
-  perturbation. For this competition, we designed and generated a novel single-cell
-  perturbational dataset in human peripheral blood mononuclear cells (PBMCs). We
-  selected 144 compounds from the Library of Integrated Network-Based Cellular Signatures
-  (LINCS) Connectivity Map dataset ([PMID: 29195078](https://pubmed.ncbi.nlm.nih.gov/29195078/))
-  and measured single-cell gene
-  expression profiles after 24 hours of treatment. The experiment was repeated in three
-  healthy human donors, and the compounds were selected based on diverse transcriptional
-  signatures observed in CD34+ hematopoietic stem cells (data not released). We performed
-  this experiment in human PBMCs because the cells are commercially available with
-  pre-obtained consent for public release and PBMCs are a primary, disease-relevant tissue
-  that contains multiple mature cell types (including T-cells, B-cells, myeloid cells,
-  and NK cells) with established markers for annotation of cell types. To supplement this
-  dataset, we also measured cells from each donor at baseline with joint scRNA and
-  single-cell chromatin accessibility measurements using the 10x Multiome assay. We hope
-  that the addition of rich multi-omic data for each donor and cell type at baseline will
-  help establish biological priors that explain the susceptibility of particular genes to
-  exhibit perturbation responses in difference biological contexts.
-
-authors:
-  - name: Artur Szałata
-    roles: [ author ]
-    info:
-      github: szalata
-      orcid: "000-0001-8413-234X"
-  - name: Robrecht Cannoodt
-    roles: [ author ]
-    info:
-      github: rcannood
-      orcid: "0000-0003-3641-729X"
-  - name: Daniel Burkhardt
-    roles: [ author ]
-    info:
-      github: dburkhardt
-      orcid: 0000-0001-7744-1363
-  - name: Malte D. Luecken
-    roles: [ author ]
-    info:
-      github: LuckyMD
-      orcid: 0000-0001-7464-7921
-  - name: Tin M. Tunjic
-    roles: [ contributor ]
-    info:
-      github: ttunja
-      orcid: 0000-0001-8842-6548
-  - name: Mengbo Wang
-    roles: [ contributor ]
-    info:
-      github: wangmengbo
-      orcid: 0000-0002-0266-9993
-  - name: Andrew Benz
-    roles: [ author ]
-    info:
-      github: andrew-benz
-      orcid: 0009-0002-8118-1861
-  - name: Tianyu Liu
-    roles: [ contributor ]
-    info:
-      github: HelloWorldLTY
-      orcid: 0000-0002-9412-6573
-  - name: Jalil Nourisa
-    roles: [ contributor ]
-    info:
-      github: janursa
-      orcid: 0000-0002-7539-4396
-  - name: Rico Meinl
-    roles: [ contributor ]
-    info:
-      github: ricomnl
-      orcid: 0000-0003-4356-6058
diff --git a/src/control_methods/ground_truth/config.vsh.yaml b/src/control_methods/ground_truth/config.vsh.yaml
index 1d229eb7..de91a874 100644
--- a/src/control_methods/ground_truth/config.vsh.yaml
+++ b/src/control_methods/ground_truth/config.vsh.yaml
@@ -1,17 +1,17 @@
 __merge__: ../../api/comp_control_method.yaml
 name: ground_truth
+label: Ground truth
+summary: "Returns the ground truth predictions."
+description: |
+  The identity function that returns the ground-truth information as the output.
 info:
-  label: Ground truth
-  summary: "Returns the ground truth predictions."
-  description: |
-    The identity function that returns the ground-truth information as the output.
   preferred_normalization: counts
 resources:
   - type: r_script
     path: script.R
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/r:1.1.0
+    image: openproblems/base_r:1.0.0
     setup:
       - type: r
         cran: [ arrow, dplyr ]
diff --git a/src/control_methods/mean_across_celltypes/config.vsh.yaml b/src/control_methods/mean_across_celltypes/config.vsh.yaml
index 8b64b3f0..a8a8661a 100644
--- a/src/control_methods/mean_across_celltypes/config.vsh.yaml
+++ b/src/control_methods/mean_across_celltypes/config.vsh.yaml
@@ -1,17 +1,16 @@
 __merge__: ../../api/comp_control_method.yaml
 name: mean_across_celltypes
-info:
-  label: Mean per cell type and gene
-  summary: Baseline method that returns mean of cell type's outcomes
-  description: |
-    Baseline method that predicts for a cell type the mean of its outcomes of all compounds.
+label: Mean per cell type and gene
+summary: Baseline method that returns mean of cell type's outcomes
+description: |
+  Baseline method that predicts for a cell type the mean of its outcomes of all compounds.
 resources:
   - type: python_script
     path: script.py
   - path: ../../utils/anndata_to_dataframe.py
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/python:1.1.0
+    image: openproblems/base_python:1.0.0
     setup:
       - type: python
         packages: [ fastparquet ]
diff --git a/src/control_methods/mean_across_compounds/config.vsh.yaml b/src/control_methods/mean_across_compounds/config.vsh.yaml
index c84a9a03..1f6a2481 100644
--- a/src/control_methods/mean_across_compounds/config.vsh.yaml
+++ b/src/control_methods/mean_across_compounds/config.vsh.yaml
@@ -1,17 +1,16 @@
 __merge__: ../../api/comp_control_method.yaml
 name: mean_across_compounds
-info:
-  label: Mean per compound and gene
-  summary: Baseline method that returns mean of compound's outcomes
-  description: |
-    Baseline method that predicts for a compound the mean of its outcomes of all samples.
+label: Mean per compound and gene
+summary: Baseline method that returns mean of compound's outcomes
+description: |
+  Baseline method that predicts for a compound the mean of its outcomes of all samples.
 resources:
   - type: python_script
     path: script.py
   - path: ../../utils/anndata_to_dataframe.py
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/python:1.1.0
+    image: openproblems/base_python:1.0.0
     setup:
       - type: python
         packages: [ fastparquet ]
diff --git a/src/control_methods/mean_outcome/config.vsh.yaml b/src/control_methods/mean_outcome/config.vsh.yaml
index 13032c86..7d1ccc6d 100644
--- a/src/control_methods/mean_outcome/config.vsh.yaml
+++ b/src/control_methods/mean_outcome/config.vsh.yaml
@@ -1,17 +1,16 @@
 __merge__: ../../api/comp_control_method.yaml
 name: mean_outcome
-info:
-  label: Mean per gene
-  summary: Baseline method that returns mean of gene's outcomes
-  description: |
-    Baseline method that predicts for a gene the mean of its outcomes of all samples.
+label: Mean per gene
+summary: Baseline method that returns mean of gene's outcomes
+description: |
+  Baseline method that predicts for a gene the mean of its outcomes of all samples.
 resources:
   - type: python_script
     path: script.py
   - path: ../../utils/anndata_to_dataframe.py
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/python:1.1.0
+    image: openproblems/base_python:1.0.0
     setup:
       - type: python
         packages: [ fastparquet ]
diff --git a/src/control_methods/sample/config.vsh.yaml b/src/control_methods/sample/config.vsh.yaml
index dd02c62e..b2c34689 100644
--- a/src/control_methods/sample/config.vsh.yaml
+++ b/src/control_methods/sample/config.vsh.yaml
@@ -1,17 +1,17 @@
 __merge__: ../../api/comp_control_method.yaml
 name: sample
+label: Sample
+summary: Sample predictions from the training data
+description: |
+  This method samples the training data to generate predictions.
 info:
-  label: Sample
-  summary: Sample predictions from the training data
-  description: |
-    This method samples the training data to generate predictions.
   preferred_normalization: counts
 resources:
   - type: r_script
     path: script.R
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/r:1.1.0
+    image: openproblems/base_r:1.0.0
     setup:
       - type: r
         cran: [ arrow, dplyr ]
diff --git a/src/control_methods/zeros/config.vsh.yaml b/src/control_methods/zeros/config.vsh.yaml
index 186f3689..b456a925 100644
--- a/src/control_methods/zeros/config.vsh.yaml
+++ b/src/control_methods/zeros/config.vsh.yaml
@@ -1,16 +1,15 @@
 __merge__: ../../api/comp_control_method.yaml
 name: zeros
-info:
-  label: Zeros
-  summary: Baseline method that predicts all zeros
-  description: |
-    Baseline method that predicts all zeros.
+label: Zeros
+summary: Baseline method that predicts all zeros
+description: |
+  Baseline method that predicts all zeros.
 resources:
   - type: python_script
     path: script.py
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/python:1.1.0
+    image: openproblems/base_python:1.0.0
     setup:
       - type: python
         packages: [ fastparquet ]
diff --git a/src/methods/jn_ap_op2/config.vsh.yaml b/src/methods/jn_ap_op2/config.vsh.yaml
index 64717d1a..91c1c19c 100644
--- a/src/methods/jn_ap_op2/config.vsh.yaml
+++ b/src/methods/jn_ap_op2/config.vsh.yaml
@@ -1,8 +1,8 @@
 __merge__: ../../api/comp_method.yaml
 
 name: jn_ap_op2
+label: JN-AP-OP2
 info:
-  label: JN-AP-OP2
   neurips2023_rank: 20
   summary: "Deep learning architecture composed of 2 modules: a sample-centric MLP and a gene-centric MLP"
   description: |
@@ -31,7 +31,7 @@ resources:
   - path: helper.py
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/pytorch_nvidia:1.1.0
+    image: openproblems/base_pytorch_nvidia:1.0.0
     setup:
       - type: python
         packages: 
diff --git a/src/methods/lgc_ensemble/config.vsh.yaml b/src/methods/lgc_ensemble/config.vsh.yaml
index 389f3ee9..5bdb4204 100644
--- a/src/methods/lgc_ensemble/config.vsh.yaml
+++ b/src/methods/lgc_ensemble/config.vsh.yaml
@@ -1,8 +1,8 @@
 __merge__: ../../api/wf_method.yaml
 
 name: lgc_ensemble
+label: LSTM-GRU-CNN Ensemble
 info:
-  label: LSTM-GRU-CNN Ensemble
   neurips2023_rank: 1
   summary: An ensemble of LSTM, GRU, and 1D CNN models
   description: |
diff --git a/src/methods/lgc_ensemble_direct/config.vsh.yaml b/src/methods/lgc_ensemble_direct/config.vsh.yaml
index 8208986b..34e27f37 100644
--- a/src/methods/lgc_ensemble_direct/config.vsh.yaml
+++ b/src/methods/lgc_ensemble_direct/config.vsh.yaml
@@ -1,8 +1,8 @@
 __merge__: ../../api/comp_method.yaml
 
 name: lgc_ensemble_direct
+label: LSTM-GRU-CNN Ensemble
 info:
-  label: LSTM-GRU-CNN Ensemble
   neurips2023_rank: 1
   summary: An ensemble of LSTM, GRU, and 1D CNN models
   description: |
@@ -54,7 +54,7 @@ resources:
     
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/pytorch_nvidia:1.1.0
+    image: openproblems/base_pytorch_nvidia:1.0.0
     setup:
       - type: python
         packages:
diff --git a/src/methods/lgc_ensemble_predict/config.vsh.yaml b/src/methods/lgc_ensemble_predict/config.vsh.yaml
index 3715a6b4..666d2d0f 100644
--- a/src/methods/lgc_ensemble_predict/config.vsh.yaml
+++ b/src/methods/lgc_ensemble_predict/config.vsh.yaml
@@ -33,7 +33,7 @@ resources:
     
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/pytorch_nvidia:1.1.0
+    image: openproblems/base_pytorch_nvidia:1.0.0
     setup:
       - type: python
         packages:
diff --git a/src/methods/lgc_ensemble_prepare/config.vsh.yaml b/src/methods/lgc_ensemble_prepare/config.vsh.yaml
index f4e14ba4..60e56b0e 100644
--- a/src/methods/lgc_ensemble_prepare/config.vsh.yaml
+++ b/src/methods/lgc_ensemble_prepare/config.vsh.yaml
@@ -56,7 +56,7 @@ resources:
     
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/pytorch_nvidia:1.1.0
+    image: openproblems/base_pytorch_nvidia:1.0.0
     setup:
       - type: python
         packages:
diff --git a/src/methods/lgc_ensemble_train/config.vsh.yaml b/src/methods/lgc_ensemble_train/config.vsh.yaml
index fe2e31a7..f963d9ad 100644
--- a/src/methods/lgc_ensemble_train/config.vsh.yaml
+++ b/src/methods/lgc_ensemble_train/config.vsh.yaml
@@ -46,7 +46,7 @@ resources:
     
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/pytorch_nvidia:1.1.0
+    image: openproblems/base_pytorch_nvidia:1.0.0
     setup:
       - type: python
         packages:
diff --git a/src/methods/nn_retraining_with_pseudolabels/config.vsh.yaml b/src/methods/nn_retraining_with_pseudolabels/config.vsh.yaml
index bb25d2cd..58f15e88 100644
--- a/src/methods/nn_retraining_with_pseudolabels/config.vsh.yaml
+++ b/src/methods/nn_retraining_with_pseudolabels/config.vsh.yaml
@@ -1,8 +1,8 @@
 __merge__: ../../api/comp_method.yaml
 
 name: nn_retraining_with_pseudolabels
+label: NN retraining with pseudolabels
 info:
-  label: NN retraining with pseudolabels
   neurips2023_rank: 3
   summary: Neural networks with pseudolabeling and ensemble modelling
   description: |
@@ -40,7 +40,7 @@ resources:
 
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/tensorflow_nvidia:1.1.0
+    image: openproblems/base_tensorflow_nvidia:1.0.0
     setup:
       - type: python
         packages: 
diff --git a/src/methods/pyboost/config.vsh.yaml b/src/methods/pyboost/config.vsh.yaml
index 87bfd9dc..fa5bea39 100644
--- a/src/methods/pyboost/config.vsh.yaml
+++ b/src/methods/pyboost/config.vsh.yaml
@@ -1,8 +1,8 @@
 __merge__: ../../api/comp_method.yaml
 
 name: pyboost
+label: Py-boost
 info:
-  label: Py-boost
   neurips2023_rank: 18
   summary: "Py-boost predicting t-scores"
   description: |
@@ -38,7 +38,7 @@ resources:
   - path: ../../utils/anndata_to_dataframe.py
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/pytorch_nvidia:1.1.0
+    image: openproblems/base_pytorch_nvidia:1.0.0
     setup:
       - type: python
         packages:
diff --git a/src/methods/scape/config.vsh.yaml b/src/methods/scape/config.vsh.yaml
index cc336bc1..14222f55 100644
--- a/src/methods/scape/config.vsh.yaml
+++ b/src/methods/scape/config.vsh.yaml
@@ -1,7 +1,7 @@
 __merge__: ../../api/comp_method.yaml
 name: scape
+label: ScAPE
 info:
-  label: ScAPE
   neurips2023_rank: 16
   summary: Neural network model for drug effect prediction
   description: |
@@ -63,7 +63,7 @@ resources:
     path: script.py
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/tensorflow_nvidia:1.1.0
+    image: openproblems/base_tensorflow_nvidia:1.0.0
     setup:
       - type: python
         packages:
diff --git a/src/methods/transformer_ensemble/config.vsh.yaml b/src/methods/transformer_ensemble/config.vsh.yaml
index 8f609c28..e77173ea 100644
--- a/src/methods/transformer_ensemble/config.vsh.yaml
+++ b/src/methods/transformer_ensemble/config.vsh.yaml
@@ -1,8 +1,8 @@
 __merge__: ../../api/comp_method.yaml
 
 name: transformer_ensemble
+label: Transformer Ensemble
 info:
-  label: Transformer Ensemble
   neurips2023_rank: 2
   summary: An ensemble of four transformer models, trained on diverse feature sets, with a cluster-based sampling strategy and robust validation for optimal performance.
   description: |
@@ -45,7 +45,7 @@ resources:
   - path: train.py
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/pytorch_nvidia:1.1.0
+    image: openproblems/base_pytorch_nvidia:1.0.0
     setup:
       - type: python
         packages:
diff --git a/src/metrics/mean_rowwise_correlation/config.vsh.yaml b/src/metrics/mean_rowwise_correlation/config.vsh.yaml
index 0c227651..faeec66a 100644
--- a/src/metrics/mean_rowwise_correlation/config.vsh.yaml
+++ b/src/metrics/mean_rowwise_correlation/config.vsh.yaml
@@ -55,7 +55,7 @@ resources:
     path: script.R
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/r:1.1.0
+    image: openproblems/base_r:1.0.0
     setup:
       - type: r
         packages: proxyC
diff --git a/src/metrics/mean_rowwise_error/config.vsh.yaml b/src/metrics/mean_rowwise_error/config.vsh.yaml
index b25a1117..dc385eb6 100644
--- a/src/metrics/mean_rowwise_error/config.vsh.yaml
+++ b/src/metrics/mean_rowwise_error/config.vsh.yaml
@@ -39,7 +39,7 @@ resources:
     path: script.R
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/r:1.1.0
+    image: openproblems/base_r:1.0.0
     setup:
       - type: r
         packages: proxyC
diff --git a/src/process_dataset/add_uns_metadata/config.vsh.yaml b/src/process_dataset/add_uns_metadata/config.vsh.yaml
index 4493c95a..66c5f6e8 100644
--- a/src/process_dataset/add_uns_metadata/config.vsh.yaml
+++ b/src/process_dataset/add_uns_metadata/config.vsh.yaml
@@ -51,7 +51,7 @@ resources:
     path: script.py
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/python:1.1.0
+    image: openproblems/base_python:1.0.0
 runners:
   - type: executable
   - type: nextflow
diff --git a/src/process_dataset/bootstrap/config.vsh.yaml b/src/process_dataset/bootstrap/config.vsh.yaml
index 5b8e081a..2fc13a96 100644
--- a/src/process_dataset/bootstrap/config.vsh.yaml
+++ b/src/process_dataset/bootstrap/config.vsh.yaml
@@ -54,7 +54,7 @@ resources:
     path: script.py
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/python:1.1.0
+    image: openproblems/base_python:1.0.0
 runners:
   - type: executable
   - type: nextflow
diff --git a/src/process_dataset/compute_pseudobulk/config.vsh.yaml b/src/process_dataset/compute_pseudobulk/config.vsh.yaml
index 71ed2f3f..f8d93fef 100644
--- a/src/process_dataset/compute_pseudobulk/config.vsh.yaml
+++ b/src/process_dataset/compute_pseudobulk/config.vsh.yaml
@@ -23,7 +23,7 @@ resources:
     path: script.py
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/python:1.1.0
+    image: openproblems/base_python:1.0.0
     setup:
       - type: python
         packages: [ pyarrow ]
diff --git a/src/process_dataset/convert_h5ad_to_parquet/config.vsh.yaml b/src/process_dataset/convert_h5ad_to_parquet/config.vsh.yaml
index cc87d0ba..64796156 100644
--- a/src/process_dataset/convert_h5ad_to_parquet/config.vsh.yaml
+++ b/src/process_dataset/convert_h5ad_to_parquet/config.vsh.yaml
@@ -39,7 +39,7 @@ resources:
   - path: ../../utils/anndata_to_dataframe.py
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/python:1.1.0
+    image: openproblems/base_python:1.0.0
     setup:
       - type: python
         packages: [ fastparquet, pandas ]
diff --git a/src/process_dataset/convert_kaggle_h5ad_to_parquet/config.vsh.yaml b/src/process_dataset/convert_kaggle_h5ad_to_parquet/config.vsh.yaml
index c65c8530..245ac5d4 100644
--- a/src/process_dataset/convert_kaggle_h5ad_to_parquet/config.vsh.yaml
+++ b/src/process_dataset/convert_kaggle_h5ad_to_parquet/config.vsh.yaml
@@ -77,7 +77,7 @@ resources:
     path: script.py
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/python:1.1.0
+    image: openproblems/base_python:1.0.0
     setup:
       - type: python
         packages: [ fastparquet, pandas ]
diff --git a/src/process_dataset/filter_obs/config.vsh.yaml b/src/process_dataset/filter_obs/config.vsh.yaml
index 3dae29db..c768d245 100644
--- a/src/process_dataset/filter_obs/config.vsh.yaml
+++ b/src/process_dataset/filter_obs/config.vsh.yaml
@@ -23,7 +23,7 @@ resources:
     path: script.R
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/r:1.1.0
+    image: openproblems/base_r:1.0.0
     setup:
       - type: r
         cran: [ dplyr, tidyr, purrr, tibble ]
diff --git a/src/process_dataset/filter_vars/config.vsh.yaml b/src/process_dataset/filter_vars/config.vsh.yaml
index fb0fbfbc..aa021f05 100644
--- a/src/process_dataset/filter_vars/config.vsh.yaml
+++ b/src/process_dataset/filter_vars/config.vsh.yaml
@@ -23,7 +23,7 @@ resources:
     path: script.R
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/r:1.1.0
+    image: openproblems/base_r:1.0.0
     setup:
       - type: r
         cran: [ edgeR, limma, dplyr, tidyr, purrr, tibble ]
diff --git a/src/process_dataset/generate_id_map/config.vsh.yaml b/src/process_dataset/generate_id_map/config.vsh.yaml
index b077035b..c90eec91 100644
--- a/src/process_dataset/generate_id_map/config.vsh.yaml
+++ b/src/process_dataset/generate_id_map/config.vsh.yaml
@@ -23,7 +23,7 @@ resources:
     path: script.py
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/python:1.1.0
+    image: openproblems/base_python:1.0.0
 runners:
   - type: executable
   - type: nextflow
diff --git a/src/process_dataset/run_limma/config.vsh.yaml b/src/process_dataset/run_limma/config.vsh.yaml
index dd328b65..b995a9aa 100644
--- a/src/process_dataset/run_limma/config.vsh.yaml
+++ b/src/process_dataset/run_limma/config.vsh.yaml
@@ -45,7 +45,7 @@ resources:
     path: script.R
 engines:
   - type: docker
-    image: ghcr.io/openproblems-bio/base_images/r:1.1.0
+    image: openproblems/base_r:1.0.0
     setup:
       - type: r
         bioc: [ edgeR, limma, dplyr, tidyr, purrr, tibble, furrr, future ]
diff --git a/src/workflows/run_benchmark/config.vsh.yaml b/src/workflows/run_benchmark/config.vsh.yaml
index f68b2542..aff8e19f 100644
--- a/src/workflows/run_benchmark/config.vsh.yaml
+++ b/src/workflows/run_benchmark/config.vsh.yaml
@@ -66,7 +66,7 @@ resources:
     path: "../../api/task_info.yaml"
 dependencies:
   - name: common/extract_metadata
-    repository: openproblemsv2
+    repository: openproblems
   - name: control_methods/zeros
   - name: control_methods/sample
   - name: control_methods/ground_truth
@@ -82,9 +82,9 @@ dependencies:
   - name: metrics/mean_rowwise_error
   - name: metrics/mean_rowwise_correlation
 repositories:
-  - name: openproblemsv2
+  - name: openproblems
     type: github
-    repo: openproblems-bio/openproblems-v2
+    repo: openproblems-bio/openproblems
     tag: main_build
 runners:
   - type: executable