CluelessNovice
commited on
Commit
•
6972977
1
Parent(s):
b440957
Update README.md
Browse files
README.md
CHANGED
@@ -1,36 +1,36 @@
|
|
1 |
-
---
|
2 |
-
license: mit
|
3 |
-
---
|
4 |
-
# Description
|
5 |
-
Structure Similarity Prediction predicts the (aligned) Local Distance Difference Test (LDDT) of the structures given an unaligned pair of proteins. Target values are computed after alignment with TM-align for all pairs of 1000 randomly sampled single-chain proteins.
|
6 |
-
|
7 |
-
# Splits
|
8 |
-
|
9 |
-
**Structure type:** PDB
|
10 |
-
|
11 |
-
The dataset is from [**ProteinShake Building datasets and benchmarks for deep learning on protein structures**](https://
|
12 |
-
|
13 |
-
- Train: 300699
|
14 |
-
- Valid: 4559
|
15 |
-
- Test: 4850
|
16 |
-
|
17 |
-
# Data format
|
18 |
-
|
19 |
-
We organize all data in LMDB format. The architecture of the databse is like:
|
20 |
-
|
21 |
-
**length:** The number of samples
|
22 |
-
|
23 |
-
**0:**
|
24 |
-
|
25 |
-
- **name_1:** The PDB ID of the protein 1
|
26 |
-
- **name_2:** The PDB ID of the protein 2
|
27 |
-
- **chain_1:** The chain ID of the protein 1
|
28 |
-
- **chain_2:** The chain ID of the protein 2
|
29 |
-
- **seq_1:** The structure-aware sequence 1
|
30 |
-
- **seq_2:** The structure-aware sequence 2
|
31 |
-
- **label:** Similarity value of the pair of proteins
|
32 |
-
|
33 |
-
**1:**
|
34 |
-
|
35 |
-
**···**
|
36 |
-
|
|
|
1 |
+
---
|
2 |
+
license: mit
|
3 |
+
---
|
4 |
+
# Description
|
5 |
+
Structure Similarity Prediction predicts the (aligned) Local Distance Difference Test (LDDT) of the structures given an unaligned pair of proteins. Target values are computed after alignment with TM-align for all pairs of 1000 randomly sampled single-chain proteins.
|
6 |
+
|
7 |
+
# Splits
|
8 |
+
|
9 |
+
**Structure type:** PDB
|
10 |
+
|
11 |
+
The dataset is from [**ProteinShake Building datasets and benchmarks for deep learning on protein structures**](https://papers.nips.cc/paper_files/paper/2023/file/b6167294ed3d6fc61e11e1592ce5cb77-Paper-Datasets_and_Benchmarks.pdf). We use the splits based on 70% structure similarity, with the number of training, validation and test set shown below:
|
12 |
+
|
13 |
+
- Train: 300699
|
14 |
+
- Valid: 4559
|
15 |
+
- Test: 4850
|
16 |
+
|
17 |
+
# Data format
|
18 |
+
|
19 |
+
We organize all data in LMDB format. The architecture of the databse is like:
|
20 |
+
|
21 |
+
**length:** The number of samples
|
22 |
+
|
23 |
+
**0:**
|
24 |
+
|
25 |
+
- **name_1:** The PDB ID of the protein 1
|
26 |
+
- **name_2:** The PDB ID of the protein 2
|
27 |
+
- **chain_1:** The chain ID of the protein 1
|
28 |
+
- **chain_2:** The chain ID of the protein 2
|
29 |
+
- **seq_1:** The structure-aware sequence 1
|
30 |
+
- **seq_2:** The structure-aware sequence 2
|
31 |
+
- **label:** Similarity value of the pair of proteins
|
32 |
+
|
33 |
+
**1:**
|
34 |
+
|
35 |
+
**···**
|
36 |
+
|