update BPTI and apo-holo table

app.py

@@ -160,9 +160,9 @@ with demo:
                     headers=protein_folding_csv.columns.to_list(),
                     datatype=['number', 'markdown'] + (len(protein_folding_csv.columns)-1) * ['number'],
                 )
-        with gr.TabItem("🏅 Multi-State Prediction Leaderboard", elem_id='multi-state-prediction-table', id=7,):
+        with gr.TabItem("🏅 Multi-State Prediction (BPTI) Leaderboard", elem_id='multi-state-prediction-bpti-table', id=7,):
             with gr.Row():
-                multi_state_prediction_csv = assign_rank_and_get_sorted_csv('data_link/multi_state_prediction.csv', 'data_rank/multi_state_prediction.csv')
+                multi_state_prediction_csv = assign_rank_and_get_sorted_csv('data_link/multi_state_prediction_bpti.csv', 'data_rank/multi_state_prediction_bpti.csv')
                 multi_state_prediction_table = gr.components.DataFrame(
                     value=convert_to_float(multi_state_prediction_csv).values,
                     height=99999,
@@ -170,19 +170,19 @@ with demo:
                     headers=multi_state_prediction_csv.columns.to_list(),
                     datatype=['number', 'markdown'] + (len(multi_state_prediction_csv.columns)-1) * ['number'],
                 )
-        # with gr.TabItem("🏅 Conformation Prediction Leaderboard", elem_id='conformation-prediction-table', id=8,):
-        #     with gr.Row():
-        #         conformation_prediction_csv = assign_rank_and_get_sorted_csv('data_link/conformation_prediction.csv', 'data_rank/conformation_prediction.csv')
-        #         conformation_prediction_table = gr.components.DataFrame(
-        #             value=convert_to_float(conformation_prediction_csv).values,
-        #             height=99999,
-        #             interactive=False,
-        #             headers=conformation_prediction_csv.columns.to_list(),
-        #             datatype=['number', 'markdown'] + (len(conformation_prediction_csv.columns)-1) * ['number'],
-        #         )
-        with gr.TabItem("🏅 Distribution Prediction Leaderboard", elem_id='distribution-prediction-table', id=8,):
+        with gr.TabItem("🏅 Multi-State Prediction (apo-holo) Leaderboard", elem_id='multi-state-prediction-apo-table', id=8,):
             with gr.Row():
-                distribution_prediction_csv = assign_rank_and_get_sorted_csv('data_link/distribution_prediction.csv', 'data_rank/distribution_prediction.csv')
+                conformation_prediction_csv = assign_rank_and_get_sorted_csv('data_link/multi_state_prediction_apo.csv', 'data_rank/multi_state_prediction_apo.csv', ignore_num=1)
+                conformation_prediction_table = gr.components.DataFrame(
+                    value=convert_to_float(conformation_prediction_csv).values,
+                    height=99999,
+                    interactive=False,
+                    headers=conformation_prediction_csv.columns.to_list(),
+                    datatype=['number', 'markdown'] + (len(conformation_prediction_csv.columns)-1) * ['number'],
+                )
+        with gr.TabItem("🏅 Distribution Prediction Leaderboard", elem_id='distribution-prediction-table', id=9,):
+            with gr.Row():
+                distribution_prediction_csv = assign_rank_and_get_sorted_csv('data_link/distribution_prediction.csv', 'data_rank/distribution_prediction.csv', ignore_num=2)
                 distribution_prediction_table = gr.components.DataFrame(
                     value=convert_to_float(distribution_prediction_csv).values,
                     height=99999,

data_link/distribution_prediction.csv

@@ -2,13 +2,13 @@ Model,Pairwise RMSD,*RMSF,Pearson r on Pairwise RMSD ↑,Pearson r on *Global RM
 MD iid,2.76,1.63,0.96,0.97,0.99,0.71,0.76,0.7,93.9,0.9,0.8,0.93,0.56,0,0.1,3.4
 MD 2.5 ns,1.54,0.98,0.89,0.85,0.85,2.21,1.57,1.93,36.6,0.62,0.45,0.64,0.24,0,0.1,3.4
 <a href="https://github.com/bjing2016/EigenFold"> EigenFold </a>,5.96,NaN,-0.04,NaN,NaN,NaN,2.35,7.96,12.2,0.36,0.18,NaN,NaN,0.7,9.6,NaN
-<a href="https://www.nature.com/articles/s41586-023-06832-9"> MSA-depth256</a>,0.84,0.53,0.25,0.34,0.59,3.63,1.83,2.9,29.3,0.3,0.28,0.33,0.06,0,0.2,5.9
-<a href="https://www.nature.com/articles/s41586-023-06832-9"> MSA-depth64</a>,2.03,1.51,0.24,0.3,0.57,4,1.87,3.32,18.3,0.38,0.27,0.38,0.12,0,0.2,8.4
-<a href="https://www.nature.com/articles/s41586-023-06832-9"> MSA-depth32</a>,5.71,7.96,0.07,0.17,0.53,6.12,2.5,5.67,17.1,0.39,0.24,0.36,0.15,0,0.5,13
-<a href="https://github.com/lujiarui/Str2Str">Str2Str-ODE (t=0.1)</a>,1.66,NaN,0.13,NaN,NaN,NaN,2.12,4.42,6.1,0.42,0.17,NaN,NaN,0,0.1,13.7
-<a href="https://github.com/lujiarui/Str2Str">Str2Str-ODE (t=0.3)</a>,3.15,NaN,0.12,NaN,NaN,NaN,2.23,4.75,9.8,0.41,0.17,NaN,NaN,0,0.1,14.8
-<a href="https://github.com/lujiarui/Str2Str">Str2Str-SDE (t=0.1)</a>,4.74,NaN,0.1,NaN,NaN,NaN,2.54,8.84,9.8,0.4,0.13,NaN,NaN,1.6,0.2,23
-<a href="https://github.com/lujiarui/Str2Str">Str2Str-SDE (t=0.3)</a>,7.54,NaN,0,NaN,NaN,NaN,3.29,12.28,7.3,0.35,0.13,NaN,NaN,1.5,0.2,21.4
+<a href="https://github.com/delalamo/af2_conformations"> MSA-depth256</a>,0.84,0.53,0.25,0.34,0.59,3.63,1.83,2.9,29.3,0.3,0.28,0.33,0.06,0,0.2,5.9
+<a href="https://github.com/delalamo/af2_conformations"> MSA-depth64</a>,2.03,1.51,0.24,0.3,0.57,4,1.87,3.32,18.3,0.38,0.27,0.38,0.12,0,0.2,8.4
+<a href="https://github.com/delalamo/af2_conformations"> MSA-depth32</a>,5.71,7.96,0.07,0.17,0.53,6.12,2.5,5.67,17.1,0.39,0.24,0.36,0.15,0,0.5,13
+<a href="https://github.com/lujiarui/Str2Str">Str2Str-ODE (Tmax=0.1)</a>,1.66,NaN,0.13,NaN,NaN,NaN,2.12,4.42,6.1,0.42,0.17,NaN,NaN,0,0.1,13.7
+<a href="https://github.com/lujiarui/Str2Str">Str2Str-ODE (Tmax=0.3)</a>,3.15,NaN,0.12,NaN,NaN,NaN,2.23,4.75,9.8,0.41,0.17,NaN,NaN,0,0.1,14.8
+<a href="https://github.com/lujiarui/Str2Str">Str2Str-SDE (Tmax=0.1)</a>,4.74,NaN,0.1,NaN,NaN,NaN,2.54,8.84,9.8,0.4,0.13,NaN,NaN,1.6,0.2,23
+<a href="https://github.com/lujiarui/Str2Str">Str2Str-SDE (Tmax=0.3)</a>,7.54,NaN,0,NaN,NaN,NaN,3.29,12.28,7.3,0.35,0.13,NaN,NaN,1.5,0.2,21.4
 <a href="https://github.com/bjing2016/alphaflow">AlphaFlow-PDB</a>,2.58,1.2,0.27,0.46,0.81,2.96,1.66,2.6,37.8,0.44,0.33,0.42,0.18,0,0.2,6.6
 <a href="https://github.com/bjing2016/alphaflow">AlphaFlow-MD</a>,2.88,1.63,0.53,0.66,0.85,2.68,1.53,2.28,39,0.57,0.38,0.5,0.24,0,0.2,21.7
 <a href="https://github.com/bjing2016/alphaflow">ESMFlow-PDB</a>,3,1.68,0.14,0.27,0.71,4.2,1.77,3.54,28,0.42,0.29,0.41,0.16,0,0.6,5.4

data_link/multi_state_prediction_apo.csv

@@ -0,0 +1,18 @@
+Model,apo-TM ↑,holo-TM ↑,TMens ↑,Pairwise TM,CA clash (%) ↓,CA break (%) ↓,PepBond break (%) ↓
+apo model,1.000,0.790,0.895,NaN,NaN,NaN,NaN
+<a href="https://github.com/bjing2016/EigenFold"> EigenFold </a>,0.831,0.864,0.847,0.907,3.6,0.3,NaN
+<a href="https://github.com/delalamo/af2_conformations"> MSA-depth256</a>,0.845,0.889,0.867,0.978,0.2,0.0,4.6
+<a href="https://github.com/delalamo/af2_conformations"> MSA-depth64</a>,0.844,0.883,0.863,0.950,0.2,0.0,5.7
+<a href="https://github.com/delalamo/af2_conformations"> MSA-depth32</a>,0.824,0.857,0.841,0.864,0.2,0.0,8.9
+<a href="https://github.com/lujiarui/Str2Str"> Str2Str-ODE (Tmax=0.1)</a>,0.762,0.778,0.770,0.954,0.2,0.0,14.0
+<a href="https://github.com/lujiarui/Str2Str"> Str2Str-ODE (Tmax=0.3)</a>,0.766,0.781,0.774,0.872,0.2,0.0,14.7
+<a href="https://github.com/lujiarui/Str2Str"> Str2Str-SDE (Tmax=0.1)</a>,0.682,0.693,0.688,0.760,0.2,1.5,22.6
+<a href="https://github.com/lujiarui/Str2Str"> Str2Str-SDE (Tmax=0.3)</a>,0.680,0.689,0.684,0.639,0.2,1.4,21.1
+<a href="https://github.com/bjing2016/alphaflow">AlphaFlow-PDB</a>,0.855,0.891,0.873,0.924,0.3,0.0,6.6
+<a href="https://github.com/bjing2016/alphaflow">AlphaFlow-MD</a>,0.857,0.863,0.860,0.894,0.2,0.0,20.8
+<a href="https://github.com/bjing2016/alphaflow">ESMFlow-PDB</a>,0.849,0.882,0.866,0.935,0.3,0.0,4.8
+<a href="https://github.com/bjing2016/alphaflow">ESMFlow-MD</a>,0.851,0.864,0.858,0.897,0.1,0.0,10.9
+<a href="https://github.com/bytedance/ConfDiff">ConfDiff-Open-ClsFree</a> ,0.838,0.879,0.859,0.870,0.8,0.0,5.8
+<a href="https://github.com/bytedance/ConfDiff">ConfDiff-Open-MD</a> ,0.839,0.874,0.857,0.863,0.4,0.0,6.8
+<a href="https://github.com/bytedance/ConfDiff">ConfDiff-ESM-ClsFree</a> ,0.837,0.864,0.850,0.846,0.7,0.0,4.6
+<a href="https://github.com/bytedance/ConfDiff">ConfDiff-ESM-MD</a> ,0.836,0.862,0.849,0.846,0.3,0.0,4.1

data_link/multi_state_prediction_bpti.csv

@@ -0,0 +1,17 @@
+Model,RMSDens N=10↓,RMSDens N=100↓,RMSDens N=500↓,RMSDens N=1000↓,RMSD Cluster 3 N=10↓,RMSD Cluster 3 N=100↓,RMSD Cluster 3 N=500↓,RMSD Cluster 3 N=1000↓,Pairwise RMSD,CA clash (%)↓,CA break (%)↓,PepBond break (%)↓
+<a href="https://github.com/bjing2016/EigenFold"> EigenFold </a>,1.56,1.5,1.47,1.46,2.54,2.48,2.46,2.46,0.85,1.4,4.3,NaN
+<a href="https://github.com/delalamo/af2_conformations"> MSA-depth256</a>,1.57,1.54,1.52,1.52,2.51,2.47,2.45,2.45,0.2,0,0,9.2
+<a href="https://github.com/delalamo/af2_conformations"> MSA-depth64</a>,1.6,1.54,1.51,1.5,2.48,2.4,2.35,2.33,0.55,0,0,7.9
+<a href="https://github.com/delalamo/af2_conformations"> MSA-depth32</a>,1.67,1.53,1.45,1.41,2.39,2.21,1.93,1.87,2.14,0.6,0,10.6
+<a href="https://github.com/lujiarui/Str2Str">Str2Str-ODE (Tmax=0.15)</a>,2.36,2.19,2.1,2.08,3.03,2.68,2.6,2.56,1.86,0,0,13.9
+<a href="https://github.com/lujiarui/Str2Str">Str2Str-SDE (Tmax=0.15)</a>,2.83,2.48,2.28,2.25,3.42,2.92,2.52,2.48,3.6,0.3,0,16
+<a href="https://github.com/bjing2016/alphaflow">AlphaFlow-PDB</a>,1.53,1.45,1.42,1.41,2.48,2.43,2.41,2.4,0.86,0,0,13.2
+<a href="https://github.com/bjing2016/alphaflow">AlphaFlow-MD</a>,1.74,1.51,1.45,1.43,2.44,2.32,2.28,2.24,1.26,0,0.1,26.2
+<a href="https://github.com/bjing2016/alphaflow">ESMFlow-PDB</a>,1.61,1.49,1.44,1.42,2.47,2.41,2.37,2.35,0.74,0,0,6
+<a href="https://github.com/bjing2016/alphaflow">ESMFlow-MD</a>,1.66,1.5,1.41,1.4,2.49,2.29,2.2,2.18,1.17,0,0,14.3
+<a href="https://github.com/bytedance/ConfDiff">ConfDiff-Open-ClsFree</a>,1.65,1.48,1.41,1.37,2.56,2.3,2.16,2.03,1.77,0.5,0,5.5
+<a href="https://github.com/bytedance/ConfDiff">ConfDiff-Open-MD</a>,1.64,1.5,1.44,1.42,2.49,2.39,2.32,2.31,1.37,0.2,0,4.6
+<a href="https://github.com/bytedance/ConfDiff">ConfDiff-ESM-ClsFree</a>,1.58,1.45,1.41,1.39,2.5,2.39,2.35,2.33,1.52,0.5,0,7.5
+<a href="https://github.com/bytedance/ConfDiff">ConfDiff-ESM-MD</a>,1.61,1.47,1.42,1.4,2.45,2.32,2.26,2.24,1.42,0.1,0,5
+<a href="https://github.com/bytedance/ConfDiff">ConfDiff-ESM-Energy</a>,1.63,1.47,1.43,1.42,2.55,2.43,2.41,2.4,1.26,0.1,0,7.5
+<a href="https://github.com/bytedance/ConfDiff">ConfDiff-ESM-Force</a>,1.58,1.44,1.37,1.36,2.45,2.33,2.23,2.22,1.76,0.1,0,8.9

data_link/protein_folding.csv

@@ -1,5 +1,5 @@
 Model,TM-score ↑,RMSD ↓,GDT-TS ↑,lDDT ↑,CA clash (%) ↓,CA break (%) ↓,PepBond break (%) ↓
-<a href="https://github.com/google-deepmind/alphafold"> AlphaFold2 </a>,0.871,3.21,0.86,0.9,0.3,0,4.8
+<a href="https://github.com/google-deepmind/alphafold"> AlphaFold2 </a>,0.871,3.21,0.86,0.904,0.3,0,4.8
 <a href="https://github.com/aqlaboratory/openfold/"> OpenFold </a>,0.87,3.21,0.856,0.895,0.4,0,2
 <a href="https://github.com/uw-ipd/RoseTTAFold2"> RoseTTAFold2 </a>,0.859,3.52,0.845,0.888,0.3,0.2,5.5
 <a href="https://github.com/facebookresearch/esm"> ESMFold </a>,0.847,3.98,0.826,0.87,0.3,0,4.7

data_rank/distribution_prediction.csv

@@ -1,2 +1,2 @@
 Model,Pairwise RMSD,*RMSF,Pearson r on Pairwise RMSD ↑,Pearson r on *Global RMSF ↑,Pearson r on *Per target RMSF ↑,*RMWD ↓,MD PCA W2 ↓,Joint PCA W2 ↓,PC sim > 0.5% ↑,Weak contacts J ↑,Transient contacts J ↑,*Exposed residue J ↑,*Exposed MI matrix ρ ↑,CA break % ↓,CA clash % ↓,PepBond break % ↓
-0,-1,0,0,0,-1,1,1,1,0,0,0,0,0,0,0,0
+0,0,0,-1,-1,-1,1,1,1,-1,-1,-1,-1,-1,0,1,1

data_rank/multi_state_prediction_apo.csv

@@ -0,0 +1,2 @@
+Model,apo-TM ↑,holo-TM ↑,TMens ↑,Pairwise TM,CA clash (%) ↓,CA break (%) ↓,PepBond break (%) ↓
+0,-1,-1,-1,0,1,0,1

data_rank/multi_state_prediction_bpti.csv

@@ -0,0 +1,2 @@
+Model,RMSDens N=10↓,RMSDens N=100↓,RMSDens N=500↓,RMSDens N=1000↓,RMSD Cluster 3 N=10↓,RMSD Cluster 3 N=100↓,RMSD Cluster 3 N=500↓,RMSD Cluster 3 N=1000↓,Pairwise RMSD,CA clash (%)↓,CA break (%)↓,PepBond break (%)↓
+0,0,0,0,1,0,0,0,1,0,-1,0,-1

data_rank/protein_folding.csv

@@ -1,2 +1,2 @@
 Model,TM-score ↑,RMSD ↓,GDT-TS ↑,lDDT ↑,CA clash (%) ↓,CA break (%) ↓,PepBond break (%) ↓
-0,-1,1,-1,-1,0,0,0
+0,-1,1,-1,-1,1,0,1