cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12167592
title: Supporting data-ileum microbiome in 35 day-old Gpx1/2-DKO mice, antibiotic-treated mice and sibling non-DKO (Gpx1+/-Gpx2-/-, Gpx1-/-Gpx2+/-) mice.

description: The data files contain raw data of the abundance of bacterial operational taxonomic units (generally at genus level) for the ileum of Gpx1/2-DKO mice (35 days of age), antibiotic-treated mice and sibling Gpx1+/-Gpx2-/- and Gpx1-/-Gpx2+/- (non-DKO) mice (abundances all).<br>Comparison of the ileum microbiome of the Splenda treated control Gpx1/2-DKO mice to non-DKO mice (35 days of age) and metronidazole treated, vancomycin treated and streptomycin treated (22 days of age to 35 days of age) (NONDKO vs, Metro vs, VANCO vs and STREP vs SPLENDACTRL).<br>Comparison of the ileum microbiomes of mice cured by antibiotic treatment vs. mice with standard pathology (Cured vs Sick).<br>Comparison file of ileum microbiome of cured mice vs non-DKO mice and non-DKO mice to metronidazole treated mice (cured vs non-DKO vs met).<br>Correlations of OTU abundances and ileum pathology markers for all OTUs and all Gpx1/2-DKO mice with graphs of selected correlations for top candidates as pathology provoking OTUs (EF abundances correl-abscesses, apoptosis, crypt density, exfoliation and Paneth cell frequency). Supplemental figures S1-S8 are a condensed version of the correlation graphs. Fig. S9 shows pathology data for colon-not presented in paper. EF Lactobacillus adjusted for E. coli dilution and Fig. S10 graphs of correlations- Lactobacillus adjusted for E. coli dilution. This latter set is an effort to produce a better fit for Lactobacillus-induced pathology correlations by factoring in E. coli as a competitor for a microaerobic niche using a simple dilution model. E. coli dilutes Lactobacillus and reduces pathology from Lactobacillus as a consequence. <br>mRNA levels of Duox2 and Nox1 in ileum of control DKO and non-DKO mice and antibiotic treated DKO mice. Note, the mRNA levels are normalized only to actin with no second normalizing gene.<br>Files are in support of a manuscript in preparation-Role of the microbiota in ileitis of a mouse model of inflammatory bowel disease-glutathione peroxide isoenzymes 1 and 2-double knockout mice on a C57BL background Fong-Fong Chu<sup>1</sup>, R. Steven Esworthy<sup>2*</sup>, Binghui Shen<sup>2 </sup>and James H. Doroshow<sup>3</sup><br><sup><br></sup><b>1</b> Department of Gastroenterology and Hepatology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, 100144 China, <b>2</b><sup> </sup>Department of Cancer Genetics and Epigenetics, Beckman Research Institute, City of Hope, Duarte, CA 91010, <b>3 </b>Center for Cancer Research and Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA. <sup></sup>
DOI: 10.6084/m9.figshare.12167529
title: ActDES – a Curated Actinobacterial Database for Evolutionary Studies

description: The Actinobacteria are a large diverse phylum of bacteria, often with large genomes with a high G+C content. There is great variation in the sequence quality, equivalence of annotation and phylogenetic representation in the sequence databases meaning that evolutionary and phylogenetic studies may be challenging. To address this, we have assembled a curated, high-level, taxa specific, non-redundant database to aid detailed comparative analysis of Actinobacteria. ActDES constitutes a novel resource for the community of Actinobacterial researchers that will be useful primarily for two types of analyses: (i) comparative genomic studies - facilitated by reliable orthologs identification across a set of defined, phylogenetically representative genomes, and (ii) phylogenomic studies which will be improved by identification of gene subsets at specified taxonomic level. These studies can then act as a springboard for the study of the evolution of virulence genes, studying the evolution of metabolism and metabolic engineering target identification. <br>Data summary All genome sequences used in this study can be found in the NCBI taxonomy browser https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi and are summarised along with Accession numbers in Table S1<br>1. All other data is available on Figshare.<br>a. Perl script files<br>b. List of genomes from NCBI (Actinobacteria database.xlsx) Table S1<br>c. CVS genome annotation files including the FASTA files of nucleotide and amino acids sequences (612 individual .cvs files – folder cvs)<br>d. BLAST nucleotide database (.fasta file)<br>e. BLAST protein database (.fasta file)<br>f. Table S2 Expansion table genus level (Expansion table.xlsx Tab Genus level)<br>g. Table S2 Expansion table species level (Expansion table.xlsx Tab species level)<br>h. All data for GlcP and Glk data – blast hits from ActDES database, MUSCLE Alignment files and .nwk tree files
DOI: 10.6084/m9.figshare.12167592.v1
title: Supporting data-ileum microbiome in 35 day-old Gpx1/2-DKO mice, antibiotic-treated mice and sibling non-DKO (Gpx1+/-Gpx2-/-, Gpx1-/-Gpx2+/-) mice.

description: The data files contain raw data of the abundance of bacterial operational taxonomic units (generally at genus level) for the ileum of Gpx1/2-DKO mice (35 days of age), antibiotic-treated mice and sibling Gpx1+/-Gpx2-/- and Gpx1-/-Gpx2+/- (non-DKO) mice(abundances all).<br>Comparison of the ileum microbiome of the Splenda treated control Gpx1/2-DKO mice to non-DKO mice (35 days of age) and metronidole treated, vancomycin treated and streptomycin treated (22 days of age to 35 days of age) (NONDKO vs, Metro vs, VANCO vs and STREP vs SPLENDACTRL).<br>Comparison of the ileum microbiomes of mice cured by antibiotic treatment vs. mice with worse pathology (Cured vs Sick).<br>Comparison file of ileum microbiome of cured mice vs non-DKO mice and non-DKO mice to metronidazole treated mice (cured vs non-DKO vs met).<br>Correlations of OTU abundances and ileum pathology markers for all OTUs and all Gpx1/2-DKO mice with graphs of selected correlations for top candidates as pathology provoking OTUs (EF abundances correl-abscesses, apoptosis, crypt density, exfoliation and Paneth cell frequency).<br>Files are in support of a manuscript in preparation-Role of the microbiota in ileitis of a mouse model of inflammatory bowel disease-glutathione peroxide isoenzymes 1 and 2-double knockout mice on a C57BL background Fong-Fong Chu<sup>1</sup>, R. Steven Esworthy<sup>2*</sup>, Binghui Shen<sup>2 </sup>and James H. Doroshow<sup>3</sup><br>
DOI: 10.6084/m9.figshare.12167592.v2
title: Supporting data-ileum microbiome in 35 day-old Gpx1/2-DKO mice, antibiotic-treated mice and sibling non-DKO (Gpx1+/-Gpx2-/-, Gpx1-/-Gpx2+/-) mice.

description: The data files contain raw data of the abundance of bacterial operational taxonomic units (generally at genus level) for the ileum of Gpx1/2-DKO mice (35 days of age), antibiotic-treated mice and sibling Gpx1+/-Gpx2-/- and Gpx1-/-Gpx2+/- (non-DKO) mice (abundances all).<br>Comparison of the ileum microbiome of the Splenda treated control Gpx1/2-DKO mice to non-DKO mice (35 days of age) and metronidazole treated, vancomycin treated and streptomycin treated (22 days of age to 35 days of age) (NONDKO vs, Metro vs, VANCO vs and STREP vs SPLENDACTRL).<br>Comparison of the ileum microbiomes of mice cured by antibiotic treatment vs. mice with worse pathology (Cured vs Sick).<br>Comparison file of ileum microbiome of cured mice vs non-DKO mice and non-DKO mice to metronidazole treated mice (cured vs non-DKO vs met).<br>Correlations of OTU abundances and ileum pathology markers for all OTUs and all Gpx1/2-DKO mice with graphs of selected correlations for top candidates as pathology provoking OTUs (EF abundances correl-abscesses, apoptosis, crypt density, exfoliation and Paneth cell frequency).<br>Files are in support of a manuscript in preparation-Role of the microbiota in ileitis of a mouse model of inflammatory bowel disease-glutathione peroxide isoenzymes 1 and 2-double knockout mice on a C57BL background Fong-Fong Chu<sup>1</sup>, R. Steven Esworthy<sup>2*</sup>, Binghui Shen<sup>2 </sup>and James H. Doroshow<sup>3</sup><br>
DOI: 10.6084/m9.figshare.12167592.v4
title: Supporting data-ileum microbiome in 35 day-old Gpx1/2-DKO mice, antibiotic-treated mice and sibling non-DKO (Gpx1+/-Gpx2-/-, Gpx1-/-Gpx2+/-) mice.

description: The data files contain raw data of the abundance of bacterial operational taxonomic units (generally at genus level) for the ileum of Gpx1/2-DKO mice (35 days of age), antibiotic-treated mice and sibling Gpx1+/-Gpx2-/- and Gpx1-/-Gpx2+/- (non-DKO) mice (abundances all).<br>Comparison of the ileum microbiome of the Splenda treated control Gpx1/2-DKO mice to non-DKO mice (35 days of age) and metronidazole treated, vancomycin treated and streptomycin treated (22 days of age to 35 days of age) (NONDKO vs, Metro vs, VANCO vs and STREP vs SPLENDACTRL).<br>Comparison of the ileum microbiomes of mice cured by antibiotic treatment vs. mice with standard pathology (Cured vs Sick).<br>Comparison file of ileum microbiome of cured mice vs non-DKO mice and non-DKO mice to metronidazole treated mice (cured vs non-DKO vs met).<br>Correlations of OTU abundances and ileum pathology markers for all OTUs and all Gpx1/2-DKO mice with graphs of selected correlations for top candidates as pathology provoking OTUs (EF abundances correl-abscesses, apoptosis, crypt density, exfoliation and Paneth cell frequency). Supplemental figures S1-S8 are a condensed version of the correlation graphs. Fig. S9 shows pathology data for colon-not presented in paper. EF Lactobacillus adjusted for E. coli dilution and Fig. S10 graphs of correlations- Lactobacillus adjusted for E. coli dilution. This latter set is an effort to produce a better fit for Lactobacillus-induced pathology correlations by factoring in E. coli as a competitor for a microaerobic niche using a simple dilution model. E. coli dilutes Lactobacillus and reduces pathology from Lactobacillus as a consequence. <br>Files are in support of a manuscript in preparation-Role of the microbiota in ileitis of a mouse model of inflammatory bowel disease-glutathione peroxide isoenzymes 1 and 2-double knockout mice on a C57BL background Fong-Fong Chu<sup>1</sup>, R. Steven Esworthy<sup>2*</sup>, Binghui Shen<sup>2 </sup>and James H. Doroshow<sup>3</sup><br><sup><br></sup><b>1</b> Department of Gastroenterology and Hepatology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, 100144 China, <b>2</b><sup> </sup>Department of Cancer Genetics and Epigenetics, Beckman Research Institute, City of Hope, Duarte, CA 91010, <b>3 </b>Center for Cancer Research and Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA. <sup></sup>
DOI: 10.6084/m9.figshare.12167592.v3
title: Supporting data-ileum microbiome in 35 day-old Gpx1/2-DKO mice, antibiotic-treated mice and sibling non-DKO (Gpx1+/-Gpx2-/-, Gpx1-/-Gpx2+/-) mice.

description: The data files contain raw data of the abundance of bacterial operational taxonomic units (generally at genus level) for the ileum of Gpx1/2-DKO mice (35 days of age), antibiotic-treated mice and sibling Gpx1+/-Gpx2-/- and Gpx1-/-Gpx2+/- (non-DKO) mice (abundances all).<br>Comparison of the ileum microbiome of the Splenda treated control Gpx1/2-DKO mice to non-DKO mice (35 days of age) and metronidazole treated, vancomycin treated and streptomycin treated (22 days of age to 35 days of age) (NONDKO vs, Metro vs, VANCO vs and STREP vs SPLENDACTRL).<br>Comparison of the ileum microbiomes of mice cured by antibiotic treatment vs. mice with worse pathology (Cured vs Sick).<br>Comparison file of ileum microbiome of cured mice vs non-DKO mice and non-DKO mice to metronidazole treated mice (cured vs non-DKO vs met).<br>Correlations of OTU abundances and ileum pathology markers for all OTUs and all Gpx1/2-DKO mice with graphs of selected correlations for top candidates as pathology provoking OTUs (EF abundances correl-abscesses, apoptosis, crypt density, exfoliation and Paneth cell frequency). Supplemental figures S1-S8 are a condensed version of the corrleation graphs. Fig S9 shows pathology data for colon-not presented in paper.<br>Files are in support of a manuscript in preparation-Role of the microbiota in ileitis of a mouse model of inflammatory bowel disease-glutathione peroxide isoenzymes 1 and 2-double knockout mice on a C57BL background Fong-Fong Chu<sup>1</sup>, R. Steven Esworthy<sup>2*</sup>, Binghui Shen<sup>2 </sup>and James H. Doroshow<sup>3</sup><br><sup><br></sup><b>1</b> Department of Gastroenterology and Hepatology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, 100144 China, <b>2</b><sup> </sup>Department of Cancer Genetics and Epigenetics, Beckman Research Institute, City of Hope, Duarte, CA 91010, <b>3 </b>Center for Cancer Research and Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA. <sup></sup>
DOI: 10.6084/m9.figshare.12164307
title: Dataset for longitudinal study of perceived risk exposure

description: Dataset for longitudinal study of perceived risk exposure.
DOI: 10.6084/m9.figshare.12164307.v1
title: Dataset for longitudinal study of perceived risk exposure

description: Dataset for longitudinal study of perceived risk exposure.
DOI: 10.6084/m9.figshare.12861217
title: Müller and Garcia (Biology Letters).tnt from A paraphyletic ‘Silesauridae' as an alternative hypothesis for the initial radiation of ornithischian dinosaurs

description: Whereas ornithischian dinosaurs are well known from Jurassic and Cretaceous deposits, deciphering the origin and early evolution of the group remains one of the hardest challenges for palaeontologists. So far, there are no unequivocal records of ornithischians from Triassic beds. Here, we present an alternative evolutionary hypothesis that suggests consideration of traditional ‘silesaurids' as a group of low-diversity clades representing a stem group leading to core ornithischians (i.e. unambiguous ornithischians, such as <i>Heterodontosaurus tucki</i>). This is particularly interesting because it fills most of the ghost lineages that emerge from the Triassic. Following the present hypothesis, the lineage that encompasses the Jurassic ornithischians evolved from ‘silesaurids' during the Middle to early Late Triassic, while typical ‘silesaurids' shared the land ecosystems with their relatives until the Late Triassic, when the group completely vanished. Therefore, Ornithischia changes from an obscure to a well-documented clade in the Triassic and is represented by records from Gondwana and Laurasia. Furthermore, according to the present hypothesis, Ornithischia was the first group of dinosaurs to adopt an omnivorous/herbivorous diet. However, this behaviour was achieved as a secondary step instead of an ancestral condition for ornithischians, as the earliest member of the clade is a faunivorous taxon. This pattern was subsequently followed by sauropodomorph dinosaurs. Indeed, the present scenario favours the independent acquisition of an herbivorous diet for ornithischians and sauropodomorphs during the Triassic, whereas the previous hypotheses suggested the independent acquisition for sauropodomorphs, ornithischians, and ‘silesaurids'.
DOI: 10.6084/m9.figshare.12861217.v1
title: Müller and Garcia (Biology Letters).tnt from A paraphyletic ‘Silesauridae' as an alternative hypothesis for the initial radiation of ornithischian dinosaurs

description: Whereas ornithischian dinosaurs are well known from Jurassic and Cretaceous deposits, deciphering the origin and early evolution of the group remains one of the hardest challenges for palaeontologists. So far, there are no unequivocal records of ornithischians from Triassic beds. Here, we present an alternative evolutionary hypothesis that suggests consideration of traditional ‘silesaurids' as a group of low-diversity clades representing a stem group leading to core ornithischians (i.e. unambiguous ornithischians, such as <i>Heterodontosaurus tucki</i>). This is particularly interesting because it fills most of the ghost lineages that emerge from the Triassic. Following the present hypothesis, the lineage that encompasses the Jurassic ornithischians evolved from ‘silesaurids' during the Middle to early Late Triassic, while typical ‘silesaurids' shared the land ecosystems with their relatives until the Late Triassic, when the group completely vanished. Therefore, Ornithischia changes from an obscure to a well-documented clade in the Triassic and is represented by records from Gondwana and Laurasia. Furthermore, according to the present hypothesis, Ornithischia was the first group of dinosaurs to adopt an omnivorous/herbivorous diet. However, this behaviour was achieved as a secondary step instead of an ancestral condition for ornithischians, as the earliest member of the clade is a faunivorous taxon. This pattern was subsequently followed by sauropodomorph dinosaurs. Indeed, the present scenario favours the independent acquisition of an herbivorous diet for ornithischians and sauropodomorphs during the Triassic, whereas the previous hypotheses suggested the independent acquisition for sauropodomorphs, ornithischians, and ‘silesaurids'.
DOI: 10.6084/m9.figshare.12164295
title: All_files_dataset

description: Data inputted in the simulation were generated by two Python scripts: "GENERATE_SAMPLES.py" and "GENERATE_RESAMPLING_DATA.py".<br>1. "GENERATE_SAMPLES.py": In this Python script, we aim to generate a) "DataSet_n[N]_p[p].pickle" where N is replaced by 500 or 5000, p is replaced by 2 or 10. This Python object contains: a1. the explicative variables "X", a2. the responses "Y", a3. the knots "knots", a4. the target tail index parameters "gamma0", a5. the k-different ranndom state responses "Yk" with k=1,..,100. To read these data, you should run the following python code (take n=5000 and p=10 for example) import pickle with open('DataSet_n5000_p10.pickle', 'rb') as handle: X = pickle.load(handle) Y = pickle.load(handle) knots = pickle.load(handle) gamma0 = pickle.load(handle) Yk = pickle.load(handle)<br> b) "gridX_p[p].picke" where p is replaced by 2 or 10. This Python object contains: b1. the setting points "gridX" which correspond to (x(1)_(m1),...,x(p)_(mp)) in the paper, b2. "prefactor" corresponds to \Delta(p)x in the paper b3. "gamma0_gridX corresponds to gamma0(gridX) To read these data, you should run the following python code (take p=10 for example) import pickle with open('gridX_p10.pickle', 'rb') as handle: gridX = pickle.load(handle) prefactor = pickle.load(handle) gamma0_gridX = pickle.load(handle)<br>2. "GENERATE_RESAMPLING_DATA.py": In this Python script, we aim to generate: a) "DataSet_Resampling_n[N]_p[p]_w_replacement.pickle" where N is replaced by 500 or 5000, p is replaced by 2 or 10. This Python object contains: a1. the resampling explicative variables "X_resample", a2. the knots "knots", a3. the resampling k-different random state response "Y_resample". To read these data, you should run the following python code (take N=5000 and p=10 for example) import pickle with open('DataSet_Resampling_n5000_p10_w_replacement.pickle', 'rb') as handle: X_resample = pickle.load(handle) ignored = pickle.load(handle) Y_resample = pickle.load(handle)
DOI: 10.6084/m9.figshare.12164250
title: Rumen MAG Fasta Files

description: Fasta files associated with the rumen metagenome-assembled genomes described in the manuscript "Insights into rumen microbial biosynthetic gene cluster diversity through genome-resolved metagenomics" by Anderson et al. <br>
DOI: 10.6084/m9.figshare.12164157
title: Cancer Hallmarks genesets

description: R object containing gene sets for cancer hallmarks<br>
DOI: 10.6084/m9.figshare.12164157.v1
title: Cancer Hallmarks genesets

description: R object containing gene sets for cancer hallmarks<br>
DOI: 10.6084/m9.figshare.12164127.v2
title: Dataset and replication code for Does the neighbourhood matter for neighbourhood satisfaction?

description: These data are described in:<br>Neal, Z. P. (In press). Do neighbourhoods matter for neighbourhood satisfaction? A meta-analysis. Urban Studies.<br>
DOI: 10.6084/m9.figshare.12164127.v1
title: Dataset for Does the neighbourhood matter for neighbourhood satisfaction?

description: These data are described in:<br>Neal, Z. P. (In press). Do neighbourhoods matter for neighbourhood satisfaction? A meta-analysis. Urban Studies.<br>
DOI: 10.6084/m9.figshare.12163992
title: sphinx_004.tar.gz

description: 4/33 captcha data
DOI: 10.6084/m9.figshare.12163992.v1
title: sphinx_004.tar.gz

description: 4/33 captcha data
DOI: 10.6084/m9.figshare.12163890
title: Staphylococcus reference sequences

description: Reference sequences for the dataset used on the mSWEEP remote lecture for the course Introduction to Applied Bioinformatics at the University of Helsinki in Spring 2020. <br><br>If you use the sequences in a publication, please cite their source as Méric et al. 2015, Genome Biology and Evolution (https://academic.oup.com/gbe/article/7/5/1313/604163).<br><br>Slides and code from the lecture are available at https://version.helsinki.fi/temaklin/itab20-msweep<br>
DOI: 10.6084/m9.figshare.12163914
title: Supplemental Table S1.docx

description: <b>Supplemental table S1. </b><b>Primers used for PCR cloning of promoter/intron fragments in the pGL3-basic reporter vectors.</b>
DOI: 10.6084/m9.figshare.12163878
title: GTT-1-protein_times.csv

description: Trajectories dataTrajectories of WW domain
DOI: 10.6084/m9.figshare.12163890.v1
title: Staphylococcus reference sequences

description: Reference sequences for the dataset used on the mSWEEP remote lecture for the course Introduction to Applied Bioinformatics at the University of Helsinki in Spring 2020. <br><br>If you use the sequences in a publication, please cite their source as Méric et al. 2015, Genome Biology and Evolution (https://academic.oup.com/gbe/article/7/5/1313/604163).<br><br>Slides and code from the lecture are available at https://version.helsinki.fi/temaklin/itab20-msweep<br>
DOI: 10.6084/m9.figshare.12163869
title: GTT-1-protein-322.dcdWW domain trajectories

description: Trajectories of ww domainTrajectories dataTrajectories of WW domain
DOI: 10.6084/m9.figshare.12163872
title: GTT-1-protein-324.dcdWW domain trajectories

description: TrajectoryTrajectories of ww domainWW domain trajectoriesTrajectories dataTrajectories of WW domain
DOI: 10.6084/m9.figshare.12163875
title: GTT-1-protein-325.dcdWW domain trajectories

description: Trajectories of ww domainTrajectories dataTrajectories of WW domain
DOI: 10.6084/m9.figshare.12163878.v1
title: GTT-1-protein_times.csv

description: Trajectories dataTrajectories of WW domain
DOI: 10.6084/m9.figshare.12163914.v2
title: Supplemental Table S1.docx

description: <b>Supplemental table S1. </b><b>Primers used for PCR cloning of promoter/intron fragments in the pGL3-basic reporter vectors.</b>
DOI: 10.6084/m9.figshare.12163866
title: GTT-1-protein-323.dcdWW domain trajectories

description: Trajectories of ww domainTrajectories dataTrajectories of WW domain
DOI: 10.6084/m9.figshare.12163875.v2
title: GTT-1-protein-325.dcdWW domain trajectories

description: Trajectories of ww domainTrajectories dataTrajectories of WW domain
DOI: 10.6084/m9.figshare.12163914.v1
title: Supplemental Table 1.docx

description: <b>Supplemental table 1. </b><b>Primers used for PCR cloning of promoter/intron fragments in the pGL3-basic reporter vectors.</b>
DOI: 10.6084/m9.figshare.12163869.v2
title: GTT-1-protein-322.dcdWW domain trajectories

description: Trajectories of ww domainTrajectories dataTrajectories of WW domain
DOI: 10.6084/m9.figshare.12163875.v1
title: GTT-1-protein-325.dcdWW domain trajectories

description: Trajectories of ww domain
DOI: 10.6084/m9.figshare.12163860
title: GTT-1-protein-321.dcdWW domain trajectories

description: Trajectories of ww domainTrajectories dataTrajectories of WW domain
DOI: 10.6084/m9.figshare.12163872.v1
title: GTT-1-protein-324.dcd

description: Trajectory
DOI: 10.6084/m9.figshare.12163857
title: GTT-1-protein-320.dcdWW domain trajectories

description: Trajectories of ww domainTrajectories dataTrajectories of WW domain