Update src/about.py

src/about.py

@@ -105,8 +105,6 @@ CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
 CITATION_BUTTON_TEXT = r"""Unsal, S., Atas, H., Albayrak, M., Turhan, K., Acar, A. C., & Doğan, T. (2022). Learning functional properties of proteins with language models. *Nature Machine Intelligence, 4*(3), 227-245.
 """
 
-TASK_INFO = ["similarity", "function", "family", "affinity"]
-
 CSV_RESULT_PATH = "./src/data/results.csv"
 
 LEADERBOARD_INTRODUCTION = """
@@ -126,10 +124,37 @@ If you find PROBE useful, please consider citing our work:
 Unsal, S., Atas, H., Albayrak, M., Turhan, K., Acar, A. C., & Doğan, T. (2022). Learning functional properties of proteins with language models. *Nature Machine Intelligence, 4*(3), 227-245.
 """
 
-similarity_tasks_options = ["sparse", "200", "500"]
-function_prediction_aspect_options = ["MF", "BP", "CC", "All_Aspects"]
-function_prediction_dataset_options = ["High", "Middle", "Low", "All_Data_Sets"]
-family_prediction_dataset_options = ["nc", "uc50", "uc30", "mm15"]
+TASK_INFO = ["Semantic Similarity", "GO-Based Function Prediction", "Target Protein Family Prediction", "Protein Protein Binding Affinity"]
+similarity_tasks_options = ["Sparse Uniform", "Well Annotated 200", "Well Annotated 500"]
+function_prediction_aspect_options = ["Molecular Function", "Biological Process", "Celular Components", "All Aspects"]
+family_prediction_dataset_options = ["Not-clustered", "UniClust50", "UniClust30", "MM-seqs15"]
+
+benchmark_type_map = {
+    "Semantic Similarity":                  "similarity",
+    "GO-Based Function Prediction":         "function",
+    "Target Protein Family Prediction":     "family",
+    "Protein Protein Binding Affinity":     "affinity",
+}
+
+similarity_tasks_map = {
+    "Sparse Uniform":    "sparse",
+    "Well Annotated 200": "200",
+    "Well Annotated 500": "500",
+}
+
+function_prediction_aspect_map = {
+    "Molecular Function":    "MF",
+    "Biological Process":     "BP",
+    "Celular Components":     "CC",
+    "All Aspects":            "All_Aspects",
+}
+
+family_prediction_dataset_map = {
+    "Not-clustered":  "nc",
+    "UniClust50":   "uc50",
+    "UniClust30":   "uc30",
+    "MM-seqs15":     "mm15",
+}
 
 benchmark_specific_metrics = {
     'similarity': ['sparse_MF_correlation', 'sparse_BP_correlation', 'sparse_CC_correlation', 'sparse_Ave_correlation',