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Data generated by the research group of Claus Wilke at UT Austin.

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1 to 10 of 12 Results

Replication Data for: Learning the local landscape of protein structures with convolutional neural networks Aug 8, 2021 Loy, James, 2021, "Replication Data for: Learning the local landscape of protein structures with convolutional neural networks", https://doi.org/10.18738/T8/8HJEF9, Texas Data Repository, V2 - Three zipped archives containing a combined total of 17263 mmCIF files representing 3d protein crystal structures - One text file containing 1,455,978 JSON objects identifying a unique protein microenvironment - Each JSON object identifies a protein microenvironment using a PDB...
model12.tar.gz Aug 8, 2021 - Replication Data for: Learning the local landscape of protein structures with convolutional neural networks Gzip Archive - 14.6 MB - MD5: 41302ef8afc57f0cdb9878192ed71278 12^3 voxel tensorflow model
model20.tar.gz Aug 8, 2021 - Replication Data for: Learning the local landscape of protein structures with convolutional neural networks Gzip Archive - 89.4 MB - MD5: 1c56b35bb24763e55f70aa7a002dccf5 20^3 voxel tensorflow model
model30.tar.gz Aug 8, 2021 - Replication Data for: Learning the local landscape of protein structures with convolutional neural networks Gzip Archive - 371.6 MB - MD5: 12be8f1ab0ee1561670baaee4c93ae40 30^3 voxel tensorflow model
modCif1.tar.gz Jul 26, 2021 - Replication Data for: Learning the local landscape of protein structures with convolutional neural networks Gzip Archive - 1.4 GB - MD5: f26cf84ed2aaaee2ce49441d11391de3
modCif2.tar.gz Jul 26, 2021 - Replication Data for: Learning the local landscape of protein structures with convolutional neural networks Gzip Archive - 1.4 GB - MD5: 1066caaaf02cce9871f0a9546d76a1cf
modCif3.tar.gz Jul 26, 2021 - Replication Data for: Learning the local landscape of protein structures with convolutional neural networks Gzip Archive - 1.5 GB - MD5: c723e5aff0bb8ea98604b014442d8559
snapshots.txt Jul 26, 2021 - Replication Data for: Learning the local landscape of protein structures with convolutional neural networks Plain Text - 143.9 MB - MD5: 77aa6cb57e036c15d37f5e15d633970e
Replication Data for "Moderate amounts of epistasis are not evolutionarily stable in small populations" by Sydykova et al. Jan 3, 2020 Sydykova, Dariya K.; LaBar, Thomas; Adami, Christoph; Wilke, Claus O., 2020, "Replication Data for "Moderate amounts of epistasis are not evolutionarily stable in small populations" by Sydykova et al.", https://doi.org/10.18738/T8/GUNX76, Texas Data Repository, V1 Simulation data of small populations evolving in epistatic fitness landscapes. The data were generated with and subsequently analyzed by the code archived at: https://doi.org/10.5281/zenodo.3558802
epistasis_evolution_data.zip Jan 3, 2020 - Replication Data for "Moderate amounts of epistasis are not evolutionarily stable in small populations" by Sydykova et al. ZIP Archive - 258.6 MB - MD5: be21967dc9acb1b9ebb41a0e2f70a2eb ZIP archive of simulation data for both fixed-q and evolving-q simulations.

Replication Data for: Learning the local landscape of protein structures with convolutional neural networks

Aug 8, 2021

Loy, James, 2021, "Replication Data for: Learning the local landscape of protein structures with convolutional neural networks", https://doi.org/10.18738/T8/8HJEF9, Texas Data Repository, V2

- Three zipped archives containing a combined total of 17263 mmCIF files representing 3d protein crystal structures - One text file containing 1,455,978 JSON objects identifying a unique protein microenvironment - Each JSON object identifies a protein microenvironment using a PDB...

model12.tar.gz

Aug 8, 2021 - Replication Data for: Learning the local landscape of protein structures with convolutional neural networks

Gzip Archive - 14.6 MB -

12^3 voxel tensorflow model

model20.tar.gz

Aug 8, 2021 - Replication Data for: Learning the local landscape of protein structures with convolutional neural networks

Gzip Archive - 89.4 MB -

20^3 voxel tensorflow model

model30.tar.gz

Aug 8, 2021 - Replication Data for: Learning the local landscape of protein structures with convolutional neural networks

Gzip Archive - 371.6 MB -

30^3 voxel tensorflow model

modCif1.tar.gz

Jul 26, 2021 - Replication Data for: Learning the local landscape of protein structures with convolutional neural networks

Gzip Archive - 1.4 GB -

modCif2.tar.gz

Jul 26, 2021 - Replication Data for: Learning the local landscape of protein structures with convolutional neural networks

Gzip Archive - 1.4 GB -

modCif3.tar.gz

Jul 26, 2021 - Replication Data for: Learning the local landscape of protein structures with convolutional neural networks

Gzip Archive - 1.5 GB -

snapshots.txt

Jul 26, 2021 - Replication Data for: Learning the local landscape of protein structures with convolutional neural networks

Plain Text - 143.9 MB -

Replication Data for "Moderate amounts of epistasis are not evolutionarily stable in small populations" by Sydykova et al.

Jan 3, 2020

Sydykova, Dariya K.; LaBar, Thomas; Adami, Christoph; Wilke, Claus O., 2020, "Replication Data for "Moderate amounts of epistasis are not evolutionarily stable in small populations" by Sydykova et al.", https://doi.org/10.18738/T8/GUNX76, Texas Data Repository, V1

Simulation data of small populations evolving in epistatic fitness landscapes. The data were generated with and subsequently analyzed by the code archived at: https://doi.org/10.5281/zenodo.3558802

epistasis_evolution_data.zip

Jan 3, 2020 - Replication Data for "Moderate amounts of epistasis are not evolutionarily stable in small populations" by Sydykova et al.

ZIP Archive - 258.6 MB -

ZIP archive of simulation data for both fixed-q and evolving-q simulations.

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