Upload README.md

README.md

@@ -1,40 +1,109 @@
----
-license: cc-by-nc-4.0
-dataset_info:
-  features:
-  - name: accession
-    dtype: string
-  - name: name
-    dtype: string
-  - name: Full Name
-    dtype: string
-  - name: taxon
-    dtype: string
-  - name: sequence
-    dtype: string
-  - name: function
-    dtype: string
-  - name: AlphaFoldDB
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 168911398
-    num_examples: 248315
-  - name: test
-    num_bytes: 3470418
-    num_examples: 4203
-  - name: validation
-    num_bytes: 3443875
-    num_examples: 4172
-  download_size: 134650306
-  dataset_size: 175825691
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
-  - split: validation
-    path: data/validation-*
----
+---
+license: cc-by-nc-4.0
+dataset_info:
+  features:
+    - name: accession
+      dtype: string
+    - name: name
+      dtype: string
+    - name: Full Name
+      dtype: string
+    - name: taxon
+      dtype: string
+    - name: sequence
+      dtype: string
+    - name: function
+      dtype: string
+    - name: AlphaFoldDB
+      dtype: string
+  splits:
+    - name: train
+      num_bytes: 168911398
+      num_examples: 248315
+    - name: test
+      num_bytes: 3470418
+      num_examples: 4203
+    - name: validation
+      num_bytes: 3443875
+      num_examples: 4172
+  download_size: 134650306
+  dataset_size: 175825691
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: data/train-*
+      - split: test
+        path: data/test-*
+      - split: validation
+        path: data/validation-*
+---
+
+
+
+# Dataset Card for Prot2Text-Data
+
+
+## Dataset Description
+
+This dataset is designed for training the Prot2Text framework. It  contains information for 256,690 proteins and is comprised of three modalities:
+
+Protein sequence (amino acid sequence)
+AlphaFold accession ID
+Textual description of the protein
+The dataset is built from the SwissProt database, a component of UniProtKB Release 2022_04.
+
+## Dataset Summary
+
+Format: TSV (Tab-separated values) - expected (not explicitly mentioned)
+Splits: Train (248,315), Validation (4,172), Test (4,203)
+Size: 256,690 proteins
+Features:
+name (str): Full name of the protein
+sequence (str): Amino acid sequence of the protein
+AlphaFoldDB (str): Accession ID of the protein in AlphaFold database
+taxon (str): Species information (potentially)
+text (str): Textual description of the protein (excluding "(By Similarity)" and "PubMed")
+## Supported Tasks and Leaderboards
+
+This dataset is intended for training and evaluating models that learn relationships between protein sequences, structures, and textual descriptions. Tasks may include:
+
+Protein function prediction
+Protein structure prediction
+Text-based protein information retrieval
+## Dataset Structure
+
+#### Data Fields:
+
+* **name:** (string) codename of the protein.
+* **Full Name:** (string) Full name of the protein.
+* **sequence:** (string) Amino acid sequence of the protein.
+* **AlphaFoldDB:** (string) Accession ID of the protein in AlphaFold database.
+* **taxon:** (string) Species information for the protein.
+* **function:** (string) Textual description of the protein.
+
+
+#### Data Splits:
+
+The dataset is split into training, validation, and test sets with a maximum sequence similarity threshold of 40% within each set using the CD-HIT clustering algorithm.
+
+* **Train:** 248,315 proteins
+* **Validation:** 4,172 proteins
+* **Test:** 4,203 proteins
+
+## Considerations for Using the Data
+
+The dataset is built from a single source (SwissProt). Consider incorporating data from other sources to increase diversity.
+The textual descriptions may contain biases present in the original database. Be mindful of these biases when using the data for downstream tasks.
+
+
+### License
+We are releasing this dataset under the terms of [CC-BY-NC-4.0](https://opendatacommons.org/licenses/by/1-0/).
+
+
+### Citation
+Please cite this dataset and the original sources if you use this dataset in your work
+```none
+
+```
+