Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2019
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2019
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Additional files related to ProteinGAN execution and analysis

Authors: D. Repecka;

Additional files related to ProteinGAN execution and analysis

Abstract

Prerequisite: ProteinGAN code is cloned and conda environment created (see README.md in the ProteinGAN repository) export PYTHONPATH={path_to_repository}/src:{path_to_repository}/src/common:$PYTHONPATH cd {path_to_repository} mkdir -p data/protein cd data/protein/ Download and unzip Length_512_lab_test_37_v2.zip (contains files used to train ProteinGAN) To train: cd {path_to_repository}src/gan/ python -u -m train_gan --batch_size 64 --name x2 --steps 999999 -shuffle_buffer_size 100000 --loss_type non_saturating --discriminator_learning_rate 0.0001 --generator_learning_rate 0.0001 --dilation_rate 2 --gf_dim 44 --df_dim 30 --dataset protein/Length_512_lab_test_37_v2 --architecture gumbel --pooling conv To generate sequences: cd {path_to_repository}src/gan/ python -u -m generate --batch_size 64 --name x2 --steps 999999 -shuffle_buffer_size 100000 --loss_type non_saturating --discriminator_learning_rate 0.0001 --generator_learning_rate 0.0001 --dilation_rate 2 --n_seqs 1000 --gf_dim 44 --df_dim 30 --dataset protein/Length_512_lab_test_37_v2 --nouse_cpu --architecture gumbel --pooling conv You also can use singularity image to run ProteinGAN. Firstly build the container by running sudo singularity build image.sif image.def Secondly run the container singularity exec --bind weights:/ProteinGAN/weights --nv image.sif sh run_protein_gan.sh modify run_protein_gan.sh to run ProteinGAN with different parameters Latent Space Analysis Latent space analysis jupyter notebook. The results and all the data needed to rerun the analysis are included. latent_space_analysis.ipynb - Latent space analysis jupyter notebook. files\one - Folder containing sequences generated by varying values of input vector. files\train_sequences.fasta - Sequences used to train pGAN. latent_space_corr.tsv - Correlation values for different properties and latent space vectors Other Jackhmmer_MDH_profile.hmm - HMM profile produced by jackhmmer. Unbalanced training dataset was used as a target database and E. coli MDH was used as query sequence (Uniprot ID: P61889). The profile was used to emit HMM generated sequences.

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 129
    download downloads 78
  • 129
    views
    78
    downloads
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
download
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
Average
Average
129
78
Green