22
33# DeepInteract (ICLR 2022)
44
5- [ ![ Paper] ( http://img.shields.io/badge/paper-arxiv.2110.02423-B31B1B.svg )] ( https://openreview.net/forum?id=CS4463zx6Hi ) [ ![ DOI] ( https://zenodo.org/badge/DOI/10.5281/zenodo.5797024 .svg )] ( https://doi.org/10.5281/zenodo.5797024 )
5+ [ ![ Paper] ( http://img.shields.io/badge/paper-arxiv.2110.02423-B31B1B.svg )] ( https://openreview.net/forum?id=CS4463zx6Hi ) [ ![ DOI] ( https://zenodo.org/badge/DOI/10.5281/zenodo.6299835 .svg )] ( https://doi.org/10.5281/zenodo.6299835 )
66
77[ <img src =" https://twixes.gallerycdn.vsassets.io/extensions/twixes/pypi-assistant/1.0.3/1589834023190/Microsoft.VisualStudio.Services.Icons.Default " width =" 50 " />] ( https://pypi.org/project/DeepInteract/ )
88
@@ -248,8 +248,8 @@ Now that we know Docker is functioning properly, we can begin building our Docke
248248
249249 ```bash
250250 mkdir -p project/checkpoints
251- wget -P project/checkpoints https://zenodo.org/record/5797024 /files/LitGINI-GeoTran-DilResNet.ckpt
252- wget -P project/checkpoints https://zenodo.org/record/5797024 /files/LitGINI-GeoTran-DilResNet-DB5-Fine-Tuned.ckpt
251+ wget -P project/checkpoints https://zenodo.org/record/6299835 /files/LitGINI-GeoTran-DilResNet.ckpt
252+ wget -P project/checkpoints https://zenodo.org/record/6299835 /files/LitGINI-GeoTran-DilResNet-DB5-Fine-Tuned.ckpt
253253 ```
254254
2552553. Build the Docker image (Warning: Requires ~13GB of Space):
@@ -400,18 +400,39 @@ referenced in `project/datasets/builder/psaia_config_file_input.txt`.**
400400
401401### Download training and cross-validation DGLGraphs
402402
403- To train, retrain , or cross-validate DeepInteract models using DIPS- Plus and/ or CASP-CAPRI targets, we first need to download the preprocessed DGLGraphs from Zenodo:
403+ To train, fine-tune , or test DeepInteract models using CASP-CAPRI, DB5- Plus, or DIPS-Plus targets, we first need to download the preprocessed DGLGraphs from Zenodo:
404404
405405```bash
406- # Download and extract preprocessed DGLGraphs for DIPS- Plus and CASP-CAPRI
406+ # Download and extract preprocessed DGLGraphs for CASP-CAPRI, DB5- Plus, and DIPS-Plus
407407# Requires ~55GB of free space
408- mkdir -p project/datasets/DIPS/final
409- cd project/datasets/DIPS/final
408+ # Download CASP-CAPRI
409+ mkdir -p ../../CASP_CAPRI/final
410+ cd ../../CASP_CAPRI/final
411+ wget https://zenodo.org/record/6299835/files/final_raw_casp_capri.tar.gz
412+ wget https://zenodo.org/record/6299835/files/final_processed_casp_capri.tar.gz
413+
414+ # Extract CASP-CAPRI
415+ tar -xzf final_raw_casp_capri.tar.gz
416+ tar -xzf final_processed_casp_capri.tar.gz
417+ rm final_raw_casp_capri.tar.gz final_processed_casp_capri.tar.gz
418+
419+ # Download DB5-Plus
420+ mkdir -p ../../DB5/final
421+ cd ../../DB5/final
422+ wget https://zenodo.org/record/6299835/files/final_raw_db5.tar.gz
423+ wget https://zenodo.org/record/6299835/files/final_processed_db5.tar.gz
424+
425+ # Extract DB5-Plus
426+ tar -xzf final_raw_db5.tar.gz
427+ tar -xzf final_processed_db5.tar.gz
428+ rm final_raw_db5.tar.gz final_processed_db5.tar.gz
410429
411430# Download DIPS-Plus
412- wget https://zenodo.org/record/5797024/files/final_raw_dips.tar.gz
413- wget https://zenodo.org/record/5797024/files/final_processed_dips.tar.gz.partaa
414- wget https://zenodo.org/record/5797024/files/final_processed_dips.tar.gz.partab
431+ mkdir -p project/datasets/DIPS/final
432+ cd project/datasets/DIPS/final
433+ wget https://zenodo.org/record/6299835/files/final_raw_dips.tar.gz
434+ wget https://zenodo.org/record/6299835/files/final_processed_dips.tar.gz.partaa
435+ wget https://zenodo.org/record/6299835/files/final_processed_dips.tar.gz.partab
415436
416437# First, reassemble all processed DGLGraphs
417438# We split the (tar.gz) archive into two separate parts with
@@ -423,17 +444,6 @@ cat final_processed_dips.tar.gz.parta* >final_processed_dips.tar.gz
423444tar -xzf final_raw_dips.tar.gz
424445tar -xzf final_processed_dips.tar.gz
425446rm final_processed_dips.tar.gz.parta* final_raw_dips.tar.gz final_processed_dips.tar.gz
426-
427- # Download CASP-CAPRI
428- mkdir -p ../../CASP_CAPRI/final
429- cd ../../CASP_CAPRI/final
430- wget https://zenodo.org/record/5797024/files/final_raw_casp_capri.tar.gz
431- wget https://zenodo.org/record/5797024/files/final_processed_casp_capri.tar.gz
432-
433- # Extract CASP-CAPRI
434- tar -xzf final_raw_casp_capri.tar.gz
435- tar -xzf final_processed_casp_capri.tar.gz
436- rm final_raw_casp_capri.tar.gz final_processed_casp_capri.tar.gz
437447```
438448
439449Navigate to the project directory and run the training script with the parameters desired:
@@ -455,8 +465,8 @@ cd "$DI_DIR"
455465
456466# Download our trained model checkpoints
457467mkdir -p project/checkpoints
458- wget -P project/checkpoints https://zenodo.org/record/5797024 /files/LitGINI-GeoTran-DilResNet.ckpt
459- wget -P project/checkpoints https://zenodo.org/record/5797024 /files/LitGINI-GeoTran-DilResNet-DB5-Fine-Tuned.ckpt
468+ wget -P project/checkpoints https://zenodo.org/record/6299835 /files/LitGINI-GeoTran-DilResNet.ckpt
469+ wget -P project/checkpoints https://zenodo.org/record/6299835 /files/LitGINI-GeoTran-DilResNet-DB5-Fine-Tuned.ckpt
460470```
461471
462472### Predict interface contact probability maps
0 commit comments