cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.2483104
title: Datasets for 'Automated characterization of noise distributions in diffusion MRI data'

description: Datasets we used for the manuscript 'Automated characterization of noise distributions in diffusion MRI data'.
DOI: 10.5281/zenodo.2483105
title: Datasets for 'Automated characterization of noise distributions in diffusion MRI data'

description: Datasets we used for the manuscript 'Automated characterization of noise distributions in diffusion MRI data'.
DOI: 10.5281/zenodo.3256079
title: MACRORE_rawDataset

description: Raw database on discrete physico-chemical and nutrients sampling, physico-chemical sensor probe and plant incubations in the Réunion reef lagoon
description: raw database, database is not totally curated
DOI: 10.18430/m3.irrmc.4737
title: X-ray diffraction data for the HDAC6-x55 project
DOI: 10.18430/m3.irrmc.4924
title: X-ray diffraction data for the HDAC6-x553 project
DOI: 10.18430/m3.irrmc.4925
title: X-ray diffraction data for the HDAC6-x552 project
DOI: 10.18430/m3.irrmc.4926
title: X-ray diffraction data for the HDAC6-x551 project
DOI: 10.18430/m3.irrmc.5020
title: X-ray diffraction data for the HDAC6-x550 project
DOI: 10.18430/m3.irrmc.5154
title: X-ray diffraction data for the HDAC6-x548 project
DOI: 10.18430/m3.irrmc.5189
title: X-ray diffraction data for the HDAC6-x547 project
DOI: 10.18430/m3.irrmc.5229
title: X-ray diffraction data for the HDAC6-x549 project
DOI: 10.5281/zenodo.3256312
title: A Deep Dive into Bitcoin Mining Pools

description: Dataset retrieved and used with the code hosted here for this paper published at WEIS 2019

Abstract

Miners play a key role in cryptocurrencies such as Bitcoin: they invest substantial computational resources in processing transactions and minting new currency units. It is well known that an attacker controlling more than half of the network’s mining power could manipulate the state of the system at will. While the influence of large mining pools appears evenly split, the actual distribution of mining power within these pools and their economic relationships with other actors remain undisclosed. To this end, we conduct the first in-depth analysis of mining reward distribution within three of the four largest Bitcoin mining pools and examine their cross-pool economic relationships. Our results suggest that individual miners are simultaneously operating across all three pools and that in each analyzed pool a small number of actors (≤ 20) receives over 50% of all BTC payouts. While the extent of an operator’s control over the resources of a mining pool remains an open debate, our findings are in line with previous research, pointing out centralization tendencies in large mining pools and cryptocurrencies in general
DOI: 10.5281/zenodo.3256313
title: A Deep Dive into Bitcoin Mining Pools

description: Dataset retrieved and used with the code hosted here for this paper published at WEIS 2019

Abstract

Miners play a key role in cryptocurrencies such as Bitcoin: they invest substantial computational resources in processing transactions and minting new currency units. It is well known that an attacker controlling more than half of the network’s mining power could manipulate the state of the system at will. While the influence of large mining pools appears evenly split, the actual distribution of mining power within these pools and their economic relationships with other actors remain undisclosed. To this end, we conduct the first in-depth analysis of mining reward distribution within three of the four largest Bitcoin mining pools and examine their cross-pool economic relationships. Our results suggest that individual miners are simultaneously operating across all three pools and that in each analyzed pool a small number of actors (≤ 20) receives over 50% of all BTC payouts. While the extent of an operator’s control over the resources of a mining pool remains an open debate, our findings are in line with previous research, pointing out centralization tendencies in large mining pools and cryptocurrencies in general
DOI: 10.18430/m3.irrmc.4920
title: X-ray diffraction data for the HDAC6-x557 project
DOI: 10.18430/m3.irrmc.4921
title: X-ray diffraction data for the HDAC6-x556 project
DOI: 10.18430/m3.irrmc.4922
title: X-ray diffraction data for the HDAC6-x555 project
DOI: 10.18430/m3.irrmc.4923
title: X-ray diffraction data for the HDAC6-x554 project
DOI: 10.18430/m3.irrmc.5036
title: X-ray diffraction data for the HDAC6-x559 project
DOI: 10.18430/m3.irrmc.5037
title: X-ray diffraction data for the HDAC6-x558 project
DOI: 10.5281/zenodo.3256297
title: Preprints in biology as a fraction of the biomedical literature

description: These data and chart present an approximate calculation of the proportion of preprints in biology when compared to publications in PubMed, based on monthly figures and incorporating monthly preprint submissions (or counts) across a selection of servers relevant to biology. 

Version 1.0 of these data represents data from January 2007 until May 31, 2019 for preprint servers: arXiv q-bio, Nature Precedings, F1000Research*, PeerJ Preprints*, bioRxiv**, Winnower*, preprints.org, Wellcome Open Research*. 

* Counts may not be specific to biology preprints only; ** Counts may include all versions posted that month, so may be an overestimate for version 1 submissions.

From January 2019, data has been gathered manually by the authors, as per the methods described in the .csv here, and is included here in 'Preprints_per_month_direct_2019-01to05.csv'. Until December 2018, monthly preprint submissions data are based on those contributed by Jordan Anaya (ORCID: https://orcid.org/0000-0002-6166-4113) for PrePubMed, source: https://raw.githubusercontent.com/OmnesRes/prepub/master/analyses/preprint_data.txt; Github repository: https://github.com/OmnesRes/prepub; website: http://www.prepubmed.org). Data are not included here, they are provided from the source linked above under MIT license associated with the website code: https://github.com/OmnesRes/prepub/blob/master/LICENSE.

A live version of these data and the chart are available from this GSheet: https://docs.google.com/spreadsheets/d/1bkGEcfQcL0LpIanVqNHci1ZFY6oVNGz7IQbEugzkqkU/edit?usp=sharing. Between version updates here, please refer to this sheet for updated counts and method updates e.g. to include more servers and ensure only version 1 submissions are counted.

For more information, please contact naomi.penfold@asapbio.org.

When presenting these data and/or chart, please attribute to ASAPbio (https://asapbio.org, twitter: @ASAPbio_).
DOI: 10.18430/m3.irrmc.4354
title: X-ray diffraction data for the HDAC6-x561 project
DOI: 10.18430/m3.irrmc.4736
title: X-ray diffraction data for the HDAC6-x56 project
DOI: 10.18430/m3.irrmc.4886
title: X-ray diffraction data for the HDAC6-x560 project
DOI: 10.18430/m3.irrmc.5085
title: X-ray diffraction data for the HDAC6-x566 project
DOI: 10.18430/m3.irrmc.5087
title: X-ray diffraction data for the HDAC6-x564 project
DOI: 10.18430/m3.irrmc.5088
title: X-ray diffraction data for the HDAC6-x565 project
DOI: 10.18430/m3.irrmc.5089
title: X-ray diffraction data for the HDAC6-x562 project
DOI: 10.18430/m3.irrmc.5090
title: X-ray diffraction data for the HDAC6-x563 project
DOI: 10.5281/zenodo.3256333
title: Protein-Protein Docking for PROTAC discovery

description: My goal is to test whether structure-based approaches can guide the design of PROTACs. As a first step, I am evaluating whether protein-protein docking tools can accurately predict the interface between an E3 ligase and its target, a question recently explore by Drummond et al. This step is necessary to define the relative orientation of the chemical moiety binding the E3 ligase and the chemical moiety binding the target protein. Once we have this information, the second step will be to design PROTACs that are compatible with the relative orientation of these 2 chemical moieties. For this first protein-protein docking step, I will compare predicted structures with crystal structures of three complexes: the first bromodomain of BRD4 (BRD4<sup>BD1</sup>) bound to the E3 ligases CRBN [pdb codes 6boy and 6bnb], the second bromodomain of BRD4 (BRD4<sup>BD2</sup>) bound to the E3 ligase VHL [pdb code 5t35] and, the bromodomain of SMARCA2<sup>BD</sup> bound to the E3 ligase VHL [pdb code 6hay]. I will be using three different protein-protein docking tools: HADDOCK, Rosetta, and ICM, which all performed among the best at past CAPRI protein docking competitions.
description: Funding Acknowledgment: The SGC is a registered charity (number 1097737) that receives funds from AbbVie, Bayer Pharma AG, Boehringer Ingelheim, Canada Foundation for Innovation, Eshelman Institute for Innovation, Genome Canada through Ontario Genomics Institute [OGI-055], Innovative Medicines Initiative (EU/EFPIA) [ULTRA-DD grant no. 115766], Janssen, Merck KGaA, Darmstadt, Germany, MSD, Novartis Pharma AG, Ontario Ministry of Research, Innovation, and Science (MRIS), Pfizer, São Paulo Research Foundation-FAPESP, Takeda, and Wellcome.
DOI: 10.5281/zenodo.3256334
title: Protein-Protein Docking for PROTAC discovery

description: My goal is to test whether structure-based approaches can guide the design of PROTACs. As a first step, I am evaluating whether protein-protein docking tools can accurately predict the interface between an E3 ligase and its target, a question recently explore by Drummond et al. This step is necessary to define the relative orientation of the chemical moiety binding the E3 ligase and the chemical moiety binding the target protein. Once we have this information, the second step will be to design PROTACs that are compatible with the relative orientation of these 2 chemical moieties. For this first protein-protein docking step, I will compare predicted structures with crystal structures of three complexes: the first bromodomain of BRD4 (BRD4<sup>BD1</sup>) bound to the E3 ligases CRBN [pdb codes 6boy and 6bnb], the second bromodomain of BRD4 (BRD4<sup>BD2</sup>) bound to the E3 ligase VHL [pdb code 5t35] and, the bromodomain of SMARCA2<sup>BD</sup> bound to the E3 ligase VHL [pdb code 6hay]. I will be using three different protein-protein docking tools: HADDOCK, Rosetta, and ICM, which all performed among the best at past CAPRI protein docking competitions.
description: Funding Acknowledgment: The SGC is a registered charity (number 1097737) that receives funds from AbbVie, Bayer Pharma AG, Boehringer Ingelheim, Canada Foundation for Innovation, Eshelman Institute for Innovation, Genome Canada through Ontario Genomics Institute [OGI-055], Innovative Medicines Initiative (EU/EFPIA) [ULTRA-DD grant no. 115766], Janssen, Merck KGaA, Darmstadt, Germany, MSD, Novartis Pharma AG, Ontario Ministry of Research, Innovation, and Science (MRIS), Pfizer, São Paulo Research Foundation-FAPESP, Takeda, and Wellcome.
DOI: 10.18430/m3.irrmc.4367
title: X-ray diffraction data for the HDAC6-x571 project
DOI: 10.18430/m3.irrmc.4368
title: X-ray diffraction data for the HDAC6-x570 project
DOI: 10.18430/m3.irrmc.4369
title: X-ray diffraction data for the HDAC6-x573 project
DOI: 10.18430/m3.irrmc.4370
title: X-ray diffraction data for the HDAC6-x572 project
DOI: 10.18430/m3.irrmc.4735
title: X-ray diffraction data for the HDAC6-x57 project
DOI: 10.18430/m3.irrmc.4973
title: X-ray diffraction data for the HDAC6-x568 project
DOI: 10.18430/m3.irrmc.4975
title: X-ray diffraction data for the HDAC6-x569 project
DOI: 10.18430/m3.irrmc.5118
title: X-ray diffraction data for the HDAC6-x567 project
DOI: 10.5281/zenodo.3187536
title: Supplemental material to 'Quantifying the out-of-plane response of unreinforced masonry walls subjected to relative support motion'

description: This repository contains the results of numerical simulations along with the Matlab scripts needed to reproduce the results shown in the article: Godio M, Beyer K. Quantifying the out-of-plane response of unreinforced masonry walls subjected to relative support motion. Frattura ed Integrità Strutturale (Fracture and Structural Integrity). 2019;50:194-208. DOI:10.3221/IGF-ESIS.50.17 Version history<br> V1: datasets added to the repository<br> V2: content PDF-file added to the repository
DOI: 10.5281/zenodo.3187537
title: Supplemental material to 'Quantifying the out-of-plane response of unreinforced masonry walls subjected to relative support motion'

description: This repository contains the results of numerical simulations along with the Matlab scripts needed to reproduce the results shown in the article:


Godio, M. & Beyer, K. (2019). Quantifying the out-of-plane response of unreinforced masonry walls subjected to relative support motion. Submitted and currently under review


The repository contains two datasets:


	01_SUPPORT_MOTIONS_WITH_PHASE_SHIFT.zip contains the results from simulations on URM walls subjected to phase-shifted support motions, plus the Matlab scripts needed to reproduce Figures 5 and 6 of the article;
	02_SUPPORT_MOTIONS_WITH_RELATIVE_AMPLITUDE.zip contains the results from simulations on URM walls subjected to support motions of relative amplitude; the Matlab scripts contained in this set allow reproducing Figures 7 and 8 of the article.


The Matlab scripts can be run through the MAIN-file contained in each dataset.
DOI: 10.17632/xgk4knv2gv.1
title: Data for: Table of electronic factors for E0 electron and electron-positron pair conversion transitions

description: Theoretical conversion coefficients and E0 electronic factors for electron and electron-positron pair emission in atomic nuclei. Data is in a fixed record length binary file. Each records contains the nuclear transition energy, E0 electronic factor and conversion coefficients for E1-E5, M1-M5 multipolarities.
DOI: 10.18430/m3.irrmc.4363
title: X-ray diffraction data for the HDAC6-x575 project
DOI: 10.18430/m3.irrmc.4364
title: X-ray diffraction data for the HDAC6-x574 project
DOI: 10.18430/m3.irrmc.4652
title: X-ray diffraction data for the HDAC6-x578 project
DOI: 10.18430/m3.irrmc.4675
title: X-ray diffraction data for the HDAC6-x577 project
DOI: 10.18430/m3.irrmc.4677
title: X-ray diffraction data for the HDAC6-x576 project
DOI: 10.18430/m3.irrmc.4753
title: X-ray diffraction data for the HDAC6-x579 project
DOI: 10.25387/g3.8150759.v2
title: Supplemental Material for Kawamura and Maruyama, 2019

description: Fig S1. Photos of Edge Assay; Table S1. Number of screened genomes and isolated mutants; Fig S2. Maximum velocity and travel distance of isolated mutants; Fig S3. <i>ix241</i> and <i>ix243</i> worms show progressive locomotor decline after four backcrosses; Table S2. Lifespan Analysis; Fig S4. Greater reduction in total locomotor healthspan compared to lifespan in <i>ix243</i> worms; Table S3. Development times of isolated mutant strains; Fig S5. Strategy to identify causative mutation site; Table S4. Remaining mutations in <i>ix243</i> mutant strains; Fig S6. Wild-type <i>elpc-2</i> gene rescues progressive decline in locomotor ability of the <i>ix243</i> mutant strain; Fig S7. The Elongator complex is required to maintain adult locomotor ability; Fig S8. Expression pattern of <i>elpc-2</i> transcriptional GFP fusion; Fig S9. <i>tut-1(tm1297)</i> mutant shows progressive decline in locomotor ability; Table S5. Development times of <i>tut-1(tm1297)</i> and <i>elpc-2(ix243)</i>;<i>tut-1(tm1297)</i> mutants; Fig S10. Amino acid alignment of <i>C. elegans</i> ELPC-2 and human ELP2; Table S6. Strain list; Table S7. Primer list.<br>Figure legends and descriptions of tables are shown in "Description of Supplementary figures and tables.docx".
DOI: 10.18430/m3.irrmc.4741
title: X-ray diffraction data for the HDAC6-x58 project
DOI: 10.18430/m3.irrmc.4836
title: X-ray diffraction data for the HDAC6-x580 project
DOI: 10.18430/m3.irrmc.4839
title: X-ray diffraction data for the HDAC6-x581 project
DOI: 10.18430/m3.irrmc.4983
title: X-ray diffraction data for the HDAC6-x5 project
DOI: 10.18430/m3.irrmc.5244
title: X-ray diffraction data for the HDAC6-x584 project
DOI: 10.18430/m3.irrmc.5245
title: X-ray diffraction data for the HDAC6-x585 project
DOI: 10.18430/m3.irrmc.5246
title: X-ray diffraction data for the HDAC6-x586 project
DOI: 10.18430/m3.irrmc.5250
title: X-ray diffraction data for the HDAC6-x582 project
DOI: 10.18430/m3.irrmc.5251
title: X-ray diffraction data for the HDAC6-x583 project
DOI: 10.18430/m3.irrmc.4503
title: X-ray diffraction data for the HDAC6-x591 project
DOI: 10.18430/m3.irrmc.4740
title: X-ray diffraction data for the HDAC6-x59 project
DOI: 10.18430/m3.irrmc.4806
title: X-ray diffraction data for the HDAC6-x589 project
DOI: 10.18430/m3.irrmc.5051
title: X-ray diffraction data for the HDAC6-x590 project
DOI: 10.18430/m3.irrmc.5240
title: X-ray diffraction data for the HDAC6-x588 project
DOI: 10.18430/m3.irrmc.5247
title: X-ray diffraction data for the HDAC6-x587 project
DOI: 10.18430/m3.irrmc.4196
title: X-ray diffraction data for the SETDB1-x1 project
DOI: 10.18430/m3.irrmc.4490
title: X-ray diffraction data for the HDAC6-x595 project
DOI: 10.18430/m3.irrmc.4506
title: X-ray diffraction data for the HDAC6-x596 project
DOI: 10.18430/m3.irrmc.4512
title: X-ray diffraction data for the HDAC6-x598 project
DOI: 10.18430/m3.irrmc.5009
title: X-ray diffraction data for the HDAC6-x593 project
DOI: 10.18430/m3.irrmc.5023
title: X-ray diffraction data for the HDAC6-x592 project
DOI: 10.18430/m3.irrmc.5073
title: X-ray diffraction data for the HDAC6-x597 project
DOI: 10.18430/m3.irrmc.5126
title: X-ray diffraction data for the HDAC6-x594 project
DOI: 10.18430/m3.irrmc.5158
title: X-ray diffraction data for the HDAC6-x599 project
DOI: 10.17632/xbw4vf53dh.1
title: Data for: Self-regularization of Hamiltonian systems

description: Python scripts with an implementation of self-regularized rigid body rotation.
DOI: 10.18430/m3.irrmc.4475
title: X-ray diffraction data for the HDAC6-x60 project
DOI: 10.18430/m3.irrmc.4982
title: X-ray diffraction data for the HDAC6-x6 project
DOI: 10.18430/m3.irrmc.5148
title: X-ray diffraction data for the HDAC6-x605 project
DOI: 10.18430/m3.irrmc.5150
title: X-ray diffraction data for the HDAC6-x604 project
DOI: 10.18430/m3.irrmc.5151
title: X-ray diffraction data for the HDAC6-x603 project
DOI: 10.18430/m3.irrmc.5153
title: X-ray diffraction data for the HDAC6-x602 project
DOI: 10.18430/m3.irrmc.5156
title: X-ray diffraction data for the HDAC6-x601 project
DOI: 10.18430/m3.irrmc.5157
title: X-ray diffraction data for the HDAC6-x600 project
DOI: 10.5281/zenodo.3256347
title: Attenuation of chronic T cell responses through constitutive COX2-dependent prostanoid synthesis by lymph node fibroblasts

description: Raw data (in microsoft excel format) which were used to generate the figures in this manuscript. One worksheet per figure.
DOI: 10.5281/zenodo.3256348
title: Attenuation of chronic T cell responses through constitutive COX2-dependent prostanoid synthesis by lymph node fibroblasts

description: Raw data (in microsoft excel format) which were used to generate the figures in this manuscript. One worksheet per figure.
DOI: 10.15129/e9c1d2ea-e673-4755-831d-6d9bd383cf8e
title: Data for: "Low-voltage organic thin-film transistors based on [n]phenacenes"

description: This dataset is associated with a paper titled "Low-voltage organic thin-film transistors based on [n]phenacenes" published in Organic Electronics on 18th June, 2019, https://doi.org/10.1016/j.orgel.2019.06.021.  All experimental details are thoroughly described in the paper. All data are placed in one Excel file (version 2010) and are fully self-explanatory.
DOI: 10.18430/m3.irrmc.4430
title: X-ray diffraction data for the HDAC6-x1004 project
DOI: 10.18430/m3.irrmc.4435
title: X-ray diffraction data for the HDAC6-x610 project
DOI: 10.18430/m3.irrmc.4436
title: X-ray diffraction data for the HDAC6-x611 project
DOI: 10.18430/m3.irrmc.4437
title: X-ray diffraction data for the HDAC6-x612 project
DOI: 10.18430/m3.irrmc.4476
title: X-ray diffraction data for the HDAC6-x61 project
DOI: 10.18430/m3.irrmc.4644
title: X-ray diffraction data for the HDAC6-x10 project
DOI: 10.18430/m3.irrmc.4715
title: X-ray diffraction data for the HDAC6-x100 project
DOI: 10.18430/m3.irrmc.4756
title: X-ray diffraction data for the HDAC6-x609 project
DOI: 10.18430/m3.irrmc.4757
title: X-ray diffraction data for the HDAC6-x608 project
DOI: 10.18430/m3.irrmc.4869
title: X-ray diffraction data for the HDAC6-x613 project
DOI: 10.18430/m3.irrmc.5144
title: X-ray diffraction data for the HDAC6-x607 project
DOI: 10.18430/m3.irrmc.5146
title: X-ray diffraction data for the HDAC6-x606 project
DOI: 10.5061/dryad.kp8pb51/1
title: Dryad Item 10.5061/DRYAD.KP8PB51/1

description: (:tba)
DOI: 10.18430/m3.irrmc.4429
title: X-ray diffraction data for the HDAC6-x1005 project
DOI: 10.18430/m3.irrmc.4431
title: X-ray diffraction data for the HDAC6-x1007 project
DOI: 10.18430/m3.irrmc.4432
title: X-ray diffraction data for the HDAC6-x1006 project
DOI: 10.18430/m3.irrmc.4433
title: X-ray diffraction data for the HDAC6-x1009 project
DOI: 10.18430/m3.irrmc.4434
title: X-ray diffraction data for the HDAC6-x1008 project
DOI: 10.18430/m3.irrmc.4459
title: X-ray diffraction data for the HDAC6-x616 project
DOI: 10.18430/m3.irrmc.4463
title: X-ray diffraction data for the HDAC6-x617 project
DOI: 10.18430/m3.irrmc.4473
title: X-ray diffraction data for the HDAC6-x62 project
DOI: 10.18430/m3.irrmc.4488
title: X-ray diffraction data for the HDAC6-x618 project
DOI: 10.18430/m3.irrmc.4489
title: X-ray diffraction data for the HDAC6-x619 project
DOI: 10.18430/m3.irrmc.4800
title: X-ray diffraction data for the HDAC6-x621 project
DOI: 10.18430/m3.irrmc.4885
title: X-ray diffraction data for the HDAC6-x614 project
DOI: 10.18430/m3.irrmc.5170
title: X-ray diffraction data for the HDAC6-x615 project
DOI: 10.18430/m3.irrmc.5241
title: X-ray diffraction data for the HDAC6-x620 project
DOI: 10.5281/zenodo.3256068
title: Webis Patent Retrieval Corpus 2012 (Webis-PRA-12)

description: The Webis Patent Retrieval Corpus 2012 (Webis-PRA-12) is a corpus for studying the impact of misspelled companies on patent retrieval.

The corpus contains 14,189 different company names extracted on the basis of 2,132,825 patents granted by the United States Patent and Trademark Office (USPTO) between 2001 and 2010.
description: {"references": ["Benno Stein, Dennis Hoppe, and Tim Gollub. The Impact of Spelling Errors on Patent Search. In Walter Daelemans, editors, 13th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2012), pages 570-579, April 2012. Association for Computational Linguistics. ISBN 978-1-937284-19-0"]}
DOI: 10.5281/zenodo.3256069
title: Webis Patent Retrieval Corpus 2012 (Webis-PRA-12)

description: The Webis Patent Retrieval Corpus 2012 (Webis-PRA-12) is a corpus for studying the impact of misspelled companies on patent retrieval.

The corpus contains 14,189 different company names extracted on the basis of 2,132,825 patents granted by the United States Patent and Trademark Office (USPTO) between 2001 and 2010.
description: {"references": ["Benno Stein, Dennis Hoppe, and Tim Gollub. The Impact of Spelling Errors on Patent Search. In Walter Daelemans, editors, 13th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2012), pages 570-579, April 2012. Association for Computational Linguistics. ISBN 978-1-937284-19-0"]}
DOI: 10.18430/m3.irrmc.4474
title: X-ray diffraction data for the HDAC6-x63 project
DOI: 10.18430/m3.irrmc.4700
title: X-ray diffraction data for the HDAC6-x1012 project
DOI: 10.18430/m3.irrmc.4701
title: X-ray diffraction data for the HDAC6-x1013 project
DOI: 10.18430/m3.irrmc.4702
title: X-ray diffraction data for the HDAC6-x1010 project
DOI: 10.18430/m3.irrmc.4703
title: X-ray diffraction data for the HDAC6-x1011 project
DOI: 10.18430/m3.irrmc.4706
title: X-ray diffraction data for the HDAC6-x1014 project
DOI: 10.18430/m3.irrmc.4716
title: X-ray diffraction data for the HDAC6-x101 project
DOI: 10.18430/m3.irrmc.5236
title: X-ray diffraction data for the HDAC6-x625 project
DOI: 10.18430/m3.irrmc.5237
title: X-ray diffraction data for the HDAC6-x624 project
DOI: 10.18430/m3.irrmc.5238
title: X-ray diffraction data for the HDAC6-x627 project