Datasets:

kunikohunter
/

CatPred-DB

@@ -31,7 +31,7 @@ These datasets were curated to address the lack of standardized, high-quality be
 This dataset is intended for training, evaluating, and benchmarking machine learning models that predict enzyme kinetic parameters from protein sequences or structural features.
 ### Downstream Use
-The dataset can be used to
 ### Out-of-Scope Use
 This dataset reflects in vitro measurements and may not generalize to in vivo conditions. It should not be used as a sole basis for clinical or industrial enzyme selection without additional experimental validation.
@@ -42,82 +42,15 @@ The repository contains:
 - datasets/ – CSV files for *k*cat, *K*m, and *K*i with train/test splits
 - scripts/ – Preprocessing and utility scripts
-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-[More Information Needed]
-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-## How to Get Started with the Model
-Use the code below to get started with the model.
-[More Information Needed]
-## Training Details
-### Training Data
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-[More Information Needed]
-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-#### Preprocessing [optional]
-[More Information Needed]
-#### Training Hyperparameters
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-### Results
-[More Information Needed]
-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
-[More Information Needed]
-## Technical Specifications [optional]
-### Model Architecture and Objective
-[More Information Needed]
-### Compute Infrastructure
-[More Information Needed]
-#### Hardware
-[More Information Needed]
-#### Software
-[More Information Needed]
-## Citation [optional]
 If you use this dataset, please cite:

 This dataset is intended for training, evaluating, and benchmarking machine learning models that predict enzyme kinetic parameters from protein sequences or structural features.
 ### Downstream Use
+The dataset can be used to train or benchmark other machine learning models for enzyme kinetic parameter prediction, or to reproduce and extend the experiments described in the CatPred publication.
 ### Out-of-Scope Use
 This dataset reflects in vitro measurements and may not generalize to in vivo conditions. It should not be used as a sole basis for clinical or industrial enzyme selection without additional experimental validation.
 - datasets/ – CSV files for *k*cat, *K*m, and *K*i with train/test splits
 - scripts/ – Preprocessing and utility scripts
+## Data Fields
+Each entry typically includes:
+## Source Data
+Data was compiled and curated from public biochemical databases, including BRENDA and SABIO-RK, as described in the CatPred publication. Splits were designed to evaluate generalization to enzyme sequences dissimilar to those seen during training.
+## Citation
 If you use this dataset, please cite: