cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3213752
title: Dataset of Pedigree, genotypes, clinical and biochemical characteristics of families of Northeastern Mexico

description: This dataset combines pedigree, genotypes, clinical and biochemical data of 37 families of Northeastern Mexico. Primary reference is the article:

Gallardo‑Blanco, H.L., Villarreal‑Perez, J.Z., Cerda‑Flores, R.M., Figueroa, A., Sanchez‑Dominguez, C.N., Gutierrez‑Valverde, J.M. ... Martinez‑Garza, L.E. (2017). Genetic variants in KCNJ11, TCF7L2 and HNF4A are associated with type 2 diabetes, BMI and dyslipidemia in families of Northeastern Mexico: A pilot study. Experimental and Therapeutic Medicine, 13, 523-529. https://doi.org/10.3892/etm.2016.3990

<strong>If you use these data please cite the corresponding manuscript, which can be downloaded here:</strong>

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5348709/

https://www.spandidos-publications.com/10.3892/etm.2016.3990

This dataset contains genotypes for the following SNPs:

rs2986742

rs4846051

rs1801131

rs1801133

rs6541030

rs12130799

rs11208654

rs1137100

rs12405556

rs3118378

rs3737576

rs10923931

rs7554936

rs3737787

rs2516839

rs1040404

rs4670767

rs7578597

rs13400937

rs10496971

rs2627037

rs1801262

rs1569175

rs2975760

rs3792267

rs10510228

rs1801282

rs3856806

rs4955316

rs9809104

rs4607103

rs6548616

rs734873

rs5400

rs2030763

rs4402960

rs1513181

rs9291090

rs10010131

rs10007810

rs385194

rs1799883

rs2504853

rs7754840

rs7745461

rs1800750

rs1800629

rs361525

rs12200998

rs2397060

rs192655

rs1044498

rs4463276

rs731257

rs864745

rs32314

rs2330442

rs4717865

rs3173798

rs10954737

rs854555

rs3917542

rs662

rs705308

rs3943253

rs751141

rs1471939

rs12544346

rs13266634

rs7844723

rs2242103

rs1408801

rs10811661

rs10511828

rs12779790

rs3793791

rs4746136

rs1111875

rs10885390

rs11196175

rs7903146

rs10885406

rs12255372

rs290487

rs4918842

rs2237892

rs10839880

rs1837606

rs5210

rs5218

rs5219

rs2946788

rs11227699

rs7930460

rs1800849

rs1387153

rs948028

rs2270031

rs2416791

rs7961581

rs2070586

rs1503767

rs2269793

rs8050136

rs818386

rs2966849

rs1879488

rs757210

rs2033111

rs11652805

rs10512572

rs2125345

rs12946618

rs12946115

rs12950541

rs1885088

rs3907047

rs2071023

rs2833479

rs2833483

rs2300386

rs2835370

rs1296819

rs1892848

rs4821004
description: {"references": ["Gallardo\u2011Blanco, H.L., Villarreal\u2011Perez, J.Z., Cerda\u2011Flores, R.M., Figueroa, A., Sanchez\u2011Dominguez, C.N., Gutierrez\u2011Valverde, J.M. ... Martinez\u2011Garza, L.E. (2017). Genetic variants in KCNJ11, TCF7L2 and HNF4A are associated with type 2 diabetes, BMI and dyslipidemia in families of Northeastern Mexico: A pilot study. Experimental and Therapeutic Medicine, 13, 523-529. https://doi.org/10.3892/etm.2016.3990"]}
DOI: 10.5281/zenodo.3213753
title: Dataset of Pedigree, genotypes, clinical and biochemical characteristics of families of Northeastern Mexico

description: This dataset combines pedigree, genotypes, clinical and biochemical data of 37 families of Northeastern Mexico. Primary reference is the article:

Gallardo‑Blanco, H.L., Villarreal‑Perez, J.Z., Cerda‑Flores, R.M., Figueroa, A., Sanchez‑Dominguez, C.N., Gutierrez‑Valverde, J.M. ... Martinez‑Garza, L.E. (2017). Genetic variants in KCNJ11, TCF7L2 and HNF4A are associated with type 2 diabetes, BMI and dyslipidemia in families of Northeastern Mexico: A pilot study. Experimental and Therapeutic Medicine, 13, 523-529. https://doi.org/10.3892/etm.2016.3990

<strong>If you use these data please cite the corresponding manuscript, which can be downloaded here:</strong>

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5348709/

https://www.spandidos-publications.com/10.3892/etm.2016.3990

This dataset contains genotypes for the following SNPs:

rs2986742

rs4846051

rs1801131

rs1801133

rs6541030

rs12130799

rs11208654

rs1137100

rs12405556

rs3118378

rs3737576

rs10923931

rs7554936

rs3737787

rs2516839

rs1040404

rs4670767

rs7578597

rs13400937

rs10496971

rs2627037

rs1801262

rs1569175

rs2975760

rs3792267

rs10510228

rs1801282

rs3856806

rs4955316

rs9809104

rs4607103

rs6548616

rs734873

rs5400

rs2030763

rs4402960

rs1513181

rs9291090

rs10010131

rs10007810

rs385194

rs1799883

rs2504853

rs7754840

rs7745461

rs1800750

rs1800629

rs361525

rs12200998

rs2397060

rs192655

rs1044498

rs4463276

rs731257

rs864745

rs32314

rs2330442

rs4717865

rs3173798

rs10954737

rs854555

rs3917542

rs662

rs705308

rs3943253

rs751141

rs1471939

rs12544346

rs13266634

rs7844723

rs2242103

rs1408801

rs10811661

rs10511828

rs12779790

rs3793791

rs4746136

rs1111875

rs10885390

rs11196175

rs7903146

rs10885406

rs12255372

rs290487

rs4918842

rs2237892

rs10839880

rs1837606

rs5210

rs5218

rs5219

rs2946788

rs11227699

rs7930460

rs1800849

rs1387153

rs948028

rs2270031

rs2416791

rs7961581

rs2070586

rs1503767

rs2269793

rs8050136

rs818386

rs2966849

rs1879488

rs757210

rs2033111

rs11652805

rs10512572

rs2125345

rs12946618

rs12946115

rs12950541

rs1885088

rs3907047

rs2071023

rs2833479

rs2833483

rs2300386

rs2835370

rs1296819

rs1892848

rs4821004
description: {"references": ["Gallardo\u2011Blanco, H.L., Villarreal\u2011Perez, J.Z., Cerda\u2011Flores, R.M., Figueroa, A., Sanchez\u2011Dominguez, C.N., Gutierrez\u2011Valverde, J.M. ... Martinez\u2011Garza, L.E. (2017). Genetic variants in KCNJ11, TCF7L2 and HNF4A are associated with type 2 diabetes, BMI and dyslipidemia in families of Northeastern Mexico: A pilot study. Experimental and Therapeutic Medicine, 13, 523-529. https://doi.org/10.3892/etm.2016.3990"]}
DOI: 10.5281/zenodo.3214924
title: Data Sets of Cause-Effect Pairs

description: Data Sets of Cause-Effect Pairs first used in the following paper:

<em><strong>Answering Binary Causal Questions Through Large-Scale Text Mining: An Evaluation Using Cause-Effect Pairs from Human Experts</strong></em><br>
Oktie Hassanzadeh, Debarun Bhattacharjya, Mark Feblowitz, Kavitha Srinivas, Michael Perrone, Shirin Sohrabi, Michael Katz<br>
<strong>IJCAI 2019</strong>

<pre><code>@inproceedings{Hassanzadeh19,
  author    = {Oktie Hassanzadeh and
               Debarun Bhattacharjya and
               Mark Feblowitz and
               Kavitha Srinivas and
               Michael Perrone and
               Shirin Sohrabi and
               Michael Katz},
  title     = {Answering Binary Causal Questions Through Large-Scale Text Mining: 
               An Evaluation Using Cause-Effect Pairs from Human Experts},
  booktitle = {Proceedings of the Twenty-Eighth International Joint Conference on
               Artificial Intelligence, {IJCAI} 2019, August 10-16, 2019, Macao, China},
  year      = {2019}
}</code></pre>

See README.txt for details.

<pre>$ wc -l *
     319 ce_me_benchmark_v1.csv
     118 nato_sfa_benchmark_v1.csv
     804 risk_models_benchmark_v1.csv
    1730 semeval_benchmark_v1.csv
    2971 total

$ ls -lh * | awk '{print $5,$9}'
    23K ce_me_benchmark_v1.csv
    11K nato_sfa_benchmark_v1.csv
    73K risk_models_benchmark_v1.csv
    42K semeval_benchmark_v1.csv


NATO SFA Benchmark is created from the tables in the Appendix of the following publicly available document:
STRATEGIC FORESIGHT ANALYSIS 2017 REPORT
Links:
https://www.act.nato.int/images/stories/media/doclibrary/171004_sfa_2017_report_hr.pdf
https://www.act.nato.int/images/stories/media/doclibrary/171004_sfa_2017_report_txt.pdf
https://www.act.nato.int/futures-work


SemEval data is published under the Creative Commons Attribution 3.0 Unported license: https://creativecommons.org/licenses/by/3.0/
Details: https://docs.google.com/document/d/1QO_CnmvNRnYwNWu1-QCAeR5ToQYkXUqFeAJbdEhsq7w/preview
Original source: https://drive.google.com/file/d/0B_jQiLugGTAkMDQ5ZjZiMTUtMzQ1Yy00YWNmLWJlZDYtOWY1ZDMwY2U4YjFk/view?sort=name&layout=list&num=50


The rest of the data sets are covered by the Creative Commons: Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) license  https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode


THIS DATA IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.</pre>
description: {"references": ["https://www.act.nato.int/images/stories/media/doclibrary/171004_sfa_2017_report_hr.pdf", "https://docs.google.com/document/d/1QO_CnmvNRnYwNWu1-QCAeR5ToQYkXUqFeAJbdEhsq7w/preview"]}
DOI: 10.5281/zenodo.3214925
title: Data Sets of Cause-Effect Pairs

description: Data Sets of Cause-Effect Pairs first used in the following paper:

<em><strong>Answering Binary Causal Questions Through Large-Scale Text Mining: An Evaluation Using Cause-Effect Pairs from Human Experts</strong></em><br>
Oktie Hassanzadeh, Debarun Bhattacharjya, Mark Feblowitz, Kavitha Srinivas, Michael Perrone, Shirin Sohrabi, Michael Katz<br>
<strong>IJCAI 2019</strong>

<pre><code>@inproceedings{Hassanzadeh19,
  author    = {Oktie Hassanzadeh and
               Debarun Bhattacharjya and
               Mark Feblowitz and
               Kavitha Srinivas and
               Michael Perrone and
               Shirin Sohrabi and
               Michael Katz},
  title     = {Answering Binary Causal Questions Through Large-Scale Text Mining: 
               An Evaluation Using Cause-Effect Pairs from Human Experts},
  booktitle = {Proceedings of the Twenty-Eighth International Joint Conference on
               Artificial Intelligence, {IJCAI} 2019, August 10-16, 2019, Macao, China},
  year      = {2019}
}</code></pre>

See README.txt for details.

<pre>$ wc -l *
     319 ce_me_benchmark_v1.csv
     118 nato_sfa_benchmark_v1.csv
     804 risk_models_benchmark_v1.csv
    1730 semeval_benchmark_v1.csv
    2971 total

$ ls -lh * | awk '{print $5,$9}'
    23K ce_me_benchmark_v1.csv
    11K nato_sfa_benchmark_v1.csv
    73K risk_models_benchmark_v1.csv
    42K semeval_benchmark_v1.csv


NATO SFA Benchmark is created from the tables in the Appendix of the following publicly available document:
STRATEGIC FORESIGHT ANALYSIS 2017 REPORT
Links:
https://www.act.nato.int/images/stories/media/doclibrary/171004_sfa_2017_report_hr.pdf
https://www.act.nato.int/images/stories/media/doclibrary/171004_sfa_2017_report_txt.pdf
https://www.act.nato.int/futures-work


SemEval data is published under the Creative Commons Attribution 3.0 Unported license: https://creativecommons.org/licenses/by/3.0/
Details: https://docs.google.com/document/d/1QO_CnmvNRnYwNWu1-QCAeR5ToQYkXUqFeAJbdEhsq7w/preview
Original source: https://drive.google.com/file/d/0B_jQiLugGTAkMDQ5ZjZiMTUtMzQ1Yy00YWNmLWJlZDYtOWY1ZDMwY2U4YjFk/view?sort=name&layout=list&num=50


The rest of the data sets are covered by the Creative Commons: Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) license  https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode


THIS DATA IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.</pre>
description: {"references": ["https://www.act.nato.int/images/stories/media/doclibrary/171004_sfa_2017_report_hr.pdf", "https://docs.google.com/document/d/1QO_CnmvNRnYwNWu1-QCAeR5ToQYkXUqFeAJbdEhsq7w/preview"]}
DOI: 10.5281/zenodo.3965893
title: Equilibration simulation of a Lo/Ld phase coexistence in a PSM/DOPC/Cholesterol mixture

description: To be added.
DOI: 10.5281/zenodo.3965892
title: Equilibration simulation of a Lo/Ld phase coexistence in a PSM/DOPC/Cholesterol mixture

description: To be added.
DOI: 10.25345/c5mw7q
title: MassIVE MSV000083844 - Differential Nycodenz label free (DIA)
title: Mapping the sub cellular proteome using a differential fractionation and an orthogonal nycodenz fractionation combined with quantitative mass spectrometry using Data Independent Acquisition (DIA)
DOI: 10.5281/zenodo.3213898
title: Raw data for the generation of the FluPRINT dataset

description: Here you can find raw data downloaded from the Stanford Data Miner (https://datamt.net) that were used to build the FluPRINT database.

Please note that in total 121 CSV files are provided in 8 folders (one for each clinical study).

Files are provided in two formats: zip and 7zip (7z).

7zip is a free and open-source file archiver available for download here: https://www.7-zip.org.
DOI: 10.5281/zenodo.3213899
title: Raw data for the generation of the FluPRINT dataset

description: Here you can find raw data downloaded from the Stanford Data Miner (https://datamt.net) that were used to build the FluPRINT database.

Please note that in total 121 CSV files are provided in 8 folders (one for each clinical study).

Files are provided in two formats: zip and 7zip (7z).

7zip is a free and open-source file archiver available for download here: https://www.7-zip.org.
DOI: 10.5066/p9erlq1v
title: Louisiana Barrier Island Comprehensive Monitoring Program - 2008 to 2016 habitat change, Early Lafourche Delta Region

description: The Barrier Island Comprehensive Monitoring (BICM) program was developed by Louisiana's Coastal Protection and Restoration Authority (CPRA) and is implemented as a component of the System Wide Assessment and Monitoring Program (SWAMP). The program uses both historical data and contemporary data collections to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. Examples of BICM datasets include still and video aerial photography for documenting shoreline changes, shoreline positions, habitat mapping, land change analyses, light detection and ranging (lidar) surveys for topographic elevations, single-beam and swath bathymetry, and sediment grab samples. For more information about the BICM program, see Kindinger and others (2013). The U.S. Geological Survey, Wetland and Aquatic Research Center provides support to the BICM program through the development of habitat map products using aerial imagery and lidar elevation data and assessing change in habitats over time. These data provide a snapshot of barrier island habitats and can be combined with other past and/or future maps to monitor these valuable natural resources over time. The current effort of this habitat mapping program includes developing habitat maps for 2008 and 2015/16 for the following BICM regions: 1) West Chenier; 2) East Chenier; 3) Acadiana Bays (only Marsh Island); 4) Early Lafourche Delta; 5) Late Lafourche Delta; 6) Modern Delta (only Chaland Headland and Shell Island); and 7) Chandeleur Islands. The BICM program has developed two habitat classification schemes which include a detailed 15-class habitat scheme and a general eight-class habitat scheme. The detailed scheme was used for this habitat mapping effort and builds off the general scheme used in previous BICM habitat mapping efforts (Fearnley and others, 2009). The additional classes developed in the detailed scheme are primarily used to further delineate various dune habitats, separate marsh and mangrove, and distinguish between beach and unvegetated barrier flat habitats. The habitat change analyses in this product depict and summarize habitat change between 2008 and 2015/2016 per BICM reach. The results from these analyses are summarized in two habitat change products. The first product depicts change in land and water coverage and the second product highlights changes based on inundation zones (for example, water, intertidal-unvegetated, intertidal-vegetated, supratidal, and developed/shoreline protection). This product also includes recommended symbology for these data layers. Please see the Entity and Attribute Information section in this metadata file for the BICM barrier island habitat and change class descriptions and the Processing Steps section for information on methodology for map development.
DOI: 10.5281/zenodo.3218428
title: Development of a versatile source apportionment analysis based on positive matrix factorization: a case study of the seasonal variation of organic aerosol sources in Estonia

description: This work presents an advanced source apportionment approach that estimates the uncertainties of the positive matrix factorization model. The selection of the environmentally meaningful solutions is challenging in such models and a systematic approach to identify and sort the factors is important. We applied this method to a novel data set covering one yearly cycle at three sites in Estonia. The main results showed that biomass burning dominates in winter, while biogenic sources prevail in summer.
DOI: 10.24431/rw1k31x
title: A Dataset from Bio-Loggers Deployed on Adult Bearded Seals (Erignathus barbatus) in Kotzebue Sound, Alaska, USA (2009-2012)

description: Bearded seals (Erignathus barbatus) are one of the most important subsistence resources for the indigenous people of coastal northern and western Alaska, as well as key components of Arctic marine ecosystems. Yet, relatively little about their abundance, seasonal distribution, migrations, or foraging behaviors has been documented scientifically. Ice-associated seal populations may be negatively impacted by offshore oil and gas development as well as by climate change. Our ability to predict impacts, however, is limited by inadequate knowledge of seal population structure and foraging ecology. By working cooperatively with Alaska Native subsistence hunters we developed methods for live- capturing bearded seals in the Chukchi Sea using nets set in the shallow coastal waters where bearded seals were foraging. Capture efforts were based out of Kotzebue and various locations in the North Slope Borough from Wainwright to Barrow in June and July from 2009 to 2012. In all, 7 seals were caught (2 adults and 5 sub-adults; 4 males and three females; ranging in length and weight from 159 cm and 116 kg to 216 cm and 253 kg), all from Kotzebue Sound. Each seal was released with two different types of bio-logging devices: the SPOT5, attached to a rear flipper, provided information on the timing of hauling out and on the seal’s location for up to three years. The MK10, glued to the top of a seal’s head, provided the same information as well as data on the timing and depths of dives. MK10 deployments remained active up to ten months and were shed from the seal during the annual molt.

The data files within this dataset represent the 'raw' data obtained from the Wildlife Computers data portal. Each deployment (unique tag id + animal id combination) is provided as a zipped archive. The root folder also includes additional documentation. The various files and detailed column descriptions are described in the 'Spreadsheet-File-Descriptions.pdf' which was downloaded from Wildlife Computers (https://wildlifecomputers.com/support/downloads/). The '00_kotzeb0912_get_data.Rmd' file is an RMarkdown file that provides code and documentation of the data retrieval process. The corresponding '00_kotzeb0912_get_data.hml' file is autogenerated from the RMarkdown file.
DOI: 10.5281/zenodo.4585613
title: Dataset for the study "Seroprevalence of meningococcal serogroup C bactericidal antibodies in the Portuguese population, a decade after vaccine introduction in the National Immunisation Programme"

description: This is the dataset for the study <strong>Seroprevalence of meningococcal serogroup C bactericidal antibodies in the Portuguese population, a decade after vaccine introduction in the National Immunisation Programme</strong> by Gonçalves et al., submitted for publication on PLOS ONE.
DOI: 10.5281/zenodo.4585612
title: Dataset for the study "Seroprevalence of meningococcal serogroup C bactericidal antibodies in the Portuguese population, a decade after vaccine introduction in the National Immunisation Programme"

description: This is the dataset for the study <strong>Seroprevalence of meningococcal serogroup C bactericidal antibodies in the Portuguese population, a decade after vaccine introduction in the National Immunisation Programme</strong> by Gonçalves et al., submitted for publication on PLOS ONE.
DOI: 10.5517/ccdc.csd.cc25k89b
title: CCDC 2012591: Experimental Crystal Structure Determination

description: Related Article: Tianle Huang, Ting Wang, Yuesen Shi, Jian Chen, Xiaoyu Guo, Ruizhi Lai, Xuexin Liu, Zhouping Wu, Dongxue Peng, Longyu Wang, Hao Li, Li Hai, Yong Wu|2021|Org.Lett.|23|1548|doi:10.1021/acs.orglett.0c04155
DOI: 10.5517/ccdc.csd.cc25k8bc
title: CCDC 2012592: Experimental Crystal Structure Determination

description: Related Article: Tianle Huang, Ting Wang, Yuesen Shi, Jian Chen, Xiaoyu Guo, Ruizhi Lai, Xuexin Liu, Zhouping Wu, Dongxue Peng, Longyu Wang, Hao Li, Li Hai, Yong Wu|2021|Org.Lett.|23|1548|doi:10.1021/acs.orglett.0c04155
DOI: 10.5517/ccdc.csd.cc25k8gh
title: CCDC 2012596: Experimental Crystal Structure Determination

description: Related Article: Tianle Huang, Ting Wang, Yuesen Shi, Jian Chen, Xiaoyu Guo, Ruizhi Lai, Xuexin Liu, Zhouping Wu, Dongxue Peng, Longyu Wang, Hao Li, Li Hai, Yong Wu|2021|Org.Lett.|23|1548|doi:10.1021/acs.orglett.0c04155
DOI: 10.5517/ccdc.csd.cc25k8hj
title: CCDC 2012597: Experimental Crystal Structure Determination

description: Related Article: Tianle Huang, Ting Wang, Yuesen Shi, Jian Chen, Xiaoyu Guo, Ruizhi Lai, Xuexin Liu, Zhouping Wu, Dongxue Peng, Longyu Wang, Hao Li, Li Hai, Yong Wu|2021|Org.Lett.|23|1548|doi:10.1021/acs.orglett.0c04155
DOI: 10.5517/ccdc.csd.cc25k8cd
title: CCDC 2012593: Experimental Crystal Structure Determination

description: Related Article: Tianle Huang, Ting Wang, Yuesen Shi, Jian Chen, Xiaoyu Guo, Ruizhi Lai, Xuexin Liu, Zhouping Wu, Dongxue Peng, Longyu Wang, Hao Li, Li Hai, Yong Wu|2021|Org.Lett.|23|1548|doi:10.1021/acs.orglett.0c04155
DOI: 10.5517/ccdc.csd.cc26h1lc
title: CCDC 2040252: Experimental Crystal Structure Determination

description: Related Article: Katsuki Tanaka, Daisuke Sakamaki, Hideki Fujiwara|2021|Chem.-Eur.J.|27|4430|doi:10.1002/chem.202005005
DOI: 10.5517/ccdc.csd.cc26h1md
title: CCDC 2040253: Experimental Crystal Structure Determination

description: Related Article: Katsuki Tanaka, Daisuke Sakamaki, Hideki Fujiwara|2021|Chem.-Eur.J.|27|4430|doi:10.1002/chem.202005005
DOI: 10.5517/ccdc.csd.cc26h1nf
title: CCDC 2040254: Experimental Crystal Structure Determination

description: Related Article: Katsuki Tanaka, Daisuke Sakamaki, Hideki Fujiwara|2021|Chem.-Eur.J.|27|4430|doi:10.1002/chem.202005005
DOI: 10.5517/ccdc.csd.cc26qztr
title: CCDC 2047885: Experimental Crystal Structure Determination

description: Related Article: Kuanwei Chen, Tao Xie, Yanfang Shen, Haibing He, Xiaoli Zhao, Shuanhu Gao|2021|Org.Lett.|23|1769|doi:10.1021/acs.orglett.1c00193
DOI: 10.5517/ccdc.csd.cc26qzvs
title: CCDC 2047886: Experimental Crystal Structure Determination

description: Related Article: Kuanwei Chen, Tao Xie, Yanfang Shen, Haibing He, Xiaoli Zhao, Shuanhu Gao|2021|Org.Lett.|23|1769|doi:10.1021/acs.orglett.1c00193
DOI: 10.5517/ccdc.csd.cc21s804
title: CCDC 1900145: Experimental Crystal Structure Determination

description: Related Article: Ibuki Nakamura, Ryo Sumitani, Tomoyuki Mochida|2021|Cryst.Growth Des.|21|1861|doi:10.1021/acs.cgd.1c00004
DOI: 10.5517/ccdc.csd.cc22jrbq
title: CCDC 1922723: Experimental Crystal Structure Determination

description: Related Article: Ibuki Nakamura, Ryo Sumitani, Tomoyuki Mochida|2021|Cryst.Growth Des.|21|1861|doi:10.1021/acs.cgd.1c00004
DOI: 10.5517/ccdc.csd.cc22jrcr
title: CCDC 1922724: Experimental Crystal Structure Determination

description: Related Article: Ibuki Nakamura, Ryo Sumitani, Tomoyuki Mochida|2021|Cryst.Growth Des.|21|1861|doi:10.1021/acs.cgd.1c00004