Update README.md

README.md

@@ -162,7 +162,7 @@ task_categories:
 ---
 
 ![image.png](./OPI_logo.png)
-# Dataset Card for Open Protein Instructions (OPI)
+# Open Protein Instructions (OPI)
 
 ## Dataset Update
 The previous version of OPI dataset is based on the **release 2022_01** of UniProtKB/Swiss-Prot protein knowledgebase. At current, OPI is updated to contain the latest **release 2023_05**, which can be accessed via the dataset file [OPI_updated_160k.json](./OPI_DATA/OPI_updated_160k.json).
@@ -179,14 +179,18 @@ Reference:
 - **Leaderboard:** 
 - **Point of Contact:** 
 
-### Dataset Summary
+### Dataset Overview
 
 Open Protein Instructions(OPI) is the initial part of Open Biology Instructions(OBI) project, together with the subsequent Open Molecule Instructions(OMI), Open DNA Instructions(ODI), Open RNA Instructions(ORI) and Open Single-cell Instructions (OSCI). OBI is a project which aims to fully leverage the potential ability of Large Language Models(LLMs), especially the scientific LLMs like Galactica, to facilitate research in AI for Life Science community. While OBI is still in an early stage, we hope to provide a starting point for the community to bridge LLMs and biological domain knowledge.
 
-## Dataset Structure
+We are excited to announce the release of the OPI dataset, a curated collection of instructions covering 9 tasks for adapting LLMs to protein biology. The dataset is designed to advance LLM-driven research in the field of protein biology. We welcome contributions and enhancements to this dataset from the community.
 
-### Data Instances
+**Accessing the OPI dataset:**
+The OPI dataset is organized into the three subfolders—AP, KM, and SU—by in the [OPI_DATA](./OPI_DATA/) directory within this repository, where you can find a subset for each specific task as well as the full dataset file: [OPI_full_1.61M_train.json](./OPI_DATA/OPI_full_1.61M_train.json). f you want to merge all or several training data files of the tasks into one single training data file, please do like this:
 
+## Dataset Examples
+
+**An example of OPI training data:**
 ```
 instruction: 
     What is the EC classification of the input protein sequence based on its biological function?
@@ -200,74 +204,74 @@ input:
 output: 
     2.7.10.2
 ```
+- **An example of OPI testing data:**
+```
+{"id": "seed_task_0", "name": "EC number of price dataset from CLEAN", "instruction": "Return the EC number of the protein sequence.", "instances": [{"input": "MAIPPYPDFRSAAFLRQHLRATMAFYDPVATDASGGQFHFFLDDGTVYNTHTRHLVSATRFVVTHAMLYRTTGEARYQVGMRHALEFLRTAFLDPATGGYAWLIDWQDGRATVQDTTRHCYGMAFVMLAYARAYEAGVPEARVWLAEAFDTAEQHFWQPAAGLYADEASPDWQLTSYRGQNANMHACEAMISAFRATGERRYIERAEQLAQGICQRQAALSDRTHAPAAEGWVWEHFHADWSVDWDYNRHDRSNIFRPWGYQVGHQTEWAKLLLQLDALLPADWHLPCAQRLFDTAVERGWDAEHGGLYYGMAPDGSICDDGKYHWVQAESMAAAAVLAVRTGDARYWQWYDRIWAYCWAHFVDHEHGAWFRILHRDNRNTTREKSNAGKVDYHNMGACYDVLLWALDAPGFSKESRSAALGRP", "output": "5.3.1.7"}], "is_classification": false}
+```
 
-### Data Splits
-The OPI dataset folder structure is as follows:
+## OPI Dataset Folder Structure
 ```
 ./OPI_DATA/
-├── AP
-│   ├── Function
+└── SU
+│   ├── EC_number
 │   │   ├── test
-│   │   │   ├── CASPSimilarSeq_function_test.jsonl
-│   │   │   ├── IDFilterSeq_function_test.jsonl
-│   │   │   └── UniProtSeq_function_test.jsonl
+│   │   │   ├── CLEAN_EC_number_new_test.jsonl
+│   │   │   └── CLEAN_EC_number_price_test.jsonl
 │   │   └── train
-│   │       ├── function_description_train.json
-│   │       └── function_description_train_0.01.json
-│   ├── GO
+│   │       ├── CLEAN_EC_number_train.json
+│   ├── Fold_type
 │   │   ├── test
-│   │   │   ├── CASPSimilarSeq_go_test.jsonl
-│   │   │   ├── IDFilterSeq_go_test.jsonl
-│   │   │   └── UniProtSeq_go_test.jsonl
+│   │   │   └── fold_type_test.jsonl
 │   │   └── train
-│   │       ├── go_terms_train.json
-│   │       └── go_terms_train_0.01.json
-│   └── Keywords
+│   │       └── fold_type_train.json
+│   └── Subcellular_localization
 │       ├── test
-│       │   ├── CASPSimilarSeq_keywords_test.jsonl
-│       │   ├── IDFilterSeq_keywords_test.jsonl
-│       │   └── UniProtSeq_keywords_test.jsonl
+│       │   ├── subcell_loc_test.jsonl
 │       └── train
-│           ├── keywords_train.json
-│           └── keywords_train_0.01.json
-├── KM
-│   ├── gSymbol2Cancer
+            └── subcell_loc_train.json
+├── AP
+│   └── Keywords
 │   │   ├── test
-│   │   │   └── gene_symbol_to_cancer_test.jsonl
+│   │   │   ├── CASPSimilarSeq_keywords_test.jsonl
+│   │   │   ├── IDFilterSeq_keywords_test.jsonl
+│   │   │   └── UniProtSeq_keywords_test.jsonl
 │   │   └── train
-│   │       └── gene_symbol_to_cancer_train.json
-│   ├── gName2Cancer
+│   │       ├── keywords_train.json
+│   ├── GO
 │   │   ├── test
-│   │   │   └── gene_name_to_cancer_test.jsonl
+│   │   │   ├── CASPSimilarSeq_go_terms_test.jsonl
+│   │   │   ├── IDFilterSeq_go_terms_test.jsonl
+│   │   │   └── UniProtSeq_go_terms_test.jsonl
 │   │   └── train
-│   │       └── gene_name_to_cancer_train.json
-│   └── gSymbol2Tissue
+│   │       ├── go_terms_train.json
+│   ├── Function
 │       ├── test
-│       │   └── gene_symbol_to_tissue_test.jsonl
+│       │   ├── CASPSimilarSeq_function_test.jsonl
+│       │   ├── IDFilterSeq_function_test.jsonl
+│       │   └── UniProtSeq_function_test.jsonl
 │       └── train
-│           └── gene_symbol_to_tissue_train.json
-└── SU
-    ├── EC_number
+│           ├── function_train.json
+├── KM
+    └── gSymbol2Tissue
     │   ├── test
-    │   │   ├── CLEAN_EC_number_new_test.jsonl
-    │   │   └── CLEAN_EC_number_price_test.jsonl
+    │   │   └── gene_symbol_to_tissue_test.jsonl
     │   └── train
-    │       ├── CLEAN_EC_number_train.json
-    ├── Fold_type-Remote
+    │       └── gene_symbol_to_tissue_train.json
+    ├── gSymbol2Cancer
     │   ├── test
-    │   │   └── Remote_test.jsonl
+    │   │   └── gene_symbol_to_cancer_test.jsonl
     │   └── train
-    │       └── Remote_train.json
-    └── Subcellular_location
+    │       └── gene_symbol_to_cancer_train.json
+    ├── gName2Cancer
         ├── test
-        │   ├── location_test.jsonl
+        │   └── gene_name_to_cancer_test.jsonl
         └── train
-            └── location_train.json
+            └── gene_name_to_cancer_train.json
 ```
 
-## Dataset Creation
+## OPI Dataset Construction Pipeline
 
-The OPI dataset is curated on our own by extracting key information from [Swiss-Prot](https://www.uniprot.org/uniprotkb?facets=reviewed%3Atrue&query=%2A) database. The detailed construction pipeline is depicted in the supplementary material of our manuscript which has been submitted to NeurIPS 2023 Datasets and Benchmarks. The following figure shows the general construction process.
+The OPI dataset is curated on our own by extracting key information from [Swiss-Prot](https://www.uniprot.org/uniprotkb?facets=reviewed%3Atrue&query=%2A) database. The following figure shows the general construction process.
 ![image.png](./OPI_data.png)
 
 ## License