cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccybj1t
title: CCDC 874046: Experimental Crystal Structure Determination

description: Related Article: Kuruppanthara N. Vijayadas, Roshna V. Nair, Rupesh L. Gawade, Amol S. Kotmale, Panchami Prabhakaran, Rajesh G. Gonnade, Vedavadi G. Puranik, Pattuparambil R. Rajamohanan, Gangadhar J. Sanjayan|2013|Org.Biomol.Chem.|11|8348|doi:10.1039/C3OB41967C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccybj2v
title: CCDC 874047: Experimental Crystal Structure Determination

description: Related Article: Kuruppanthara N. Vijayadas, Roshna V. Nair, Rupesh L. Gawade, Amol S. Kotmale, Panchami Prabhakaran, Rajesh G. Gonnade, Vedavadi G. Puranik, Pattuparambil R. Rajamohanan, Gangadhar J. Sanjayan|2013|Org.Biomol.Chem.|11|8348|doi:10.1039/C3OB41967C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccybhzq
title: CCDC 874044: Experimental Crystal Structure Determination

description: Related Article: Kuruppanthara N. Vijayadas, Roshna V. Nair, Rupesh L. Gawade, Amol S. Kotmale, Panchami Prabhakaran, Rajesh G. Gonnade, Vedavadi G. Puranik, Pattuparambil R. Rajamohanan, Gangadhar J. Sanjayan|2013|Org.Biomol.Chem.|11|8348|doi:10.1039/C3OB41967C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccybj0s
title: CCDC 874045: Experimental Crystal Structure Determination

description: Related Article: Kuruppanthara N. Vijayadas, Roshna V. Nair, Rupesh L. Gawade, Amol S. Kotmale, Panchami Prabhakaran, Rajesh G. Gonnade, Vedavadi G. Puranik, Pattuparambil R. Rajamohanan, Gangadhar J. Sanjayan|2013|Org.Biomol.Chem.|11|8348|doi:10.1039/C3OB41967C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccybhxn
title: CCDC 874042: Experimental Crystal Structure Determination

description: Related Article: Kuruppanthara N. Vijayadas, Roshna V. Nair, Rupesh L. Gawade, Amol S. Kotmale, Panchami Prabhakaran, Rajesh G. Gonnade, Vedavadi G. Puranik, Pattuparambil R. Rajamohanan, Gangadhar J. Sanjayan|2013|Org.Biomol.Chem.|11|8348|doi:10.1039/C3OB41967C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccybhyp
title: CCDC 874043: Experimental Crystal Structure Determination

description: Related Article: Kuruppanthara N. Vijayadas, Roshna V. Nair, Rupesh L. Gawade, Amol S. Kotmale, Panchami Prabhakaran, Rajesh G. Gonnade, Vedavadi G. Puranik, Pattuparambil R. Rajamohanan, Gangadhar J. Sanjayan|2013|Org.Biomol.Chem.|11|8348|doi:10.1039/C3OB41967C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccybhvl
title: CCDC 874040: Experimental Crystal Structure Determination

description: Related Article: Kuruppanthara N. Vijayadas, Roshna V. Nair, Rupesh L. Gawade, Amol S. Kotmale, Panchami Prabhakaran, Rajesh G. Gonnade, Vedavadi G. Puranik, Pattuparambil R. Rajamohanan, Gangadhar J. Sanjayan|2013|Org.Biomol.Chem.|11|8348|doi:10.1039/C3OB41967C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccybhwm
title: CCDC 874041: Experimental Crystal Structure Determination

description: Related Article: Kuruppanthara N. Vijayadas, Roshna V. Nair, Rupesh L. Gawade, Amol S. Kotmale, Panchami Prabhakaran, Rajesh G. Gonnade, Vedavadi G. Puranik, Pattuparambil R. Rajamohanan, Gangadhar J. Sanjayan|2013|Org.Biomol.Chem.|11|8348|doi:10.1039/C3OB41967C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccybhtk
title: CCDC 874039: Experimental Crystal Structure Determination

description: Related Article: Kuruppanthara N. Vijayadas, Roshna V. Nair, Rupesh L. Gawade, Amol S. Kotmale, Panchami Prabhakaran, Rajesh G. Gonnade, Vedavadi G. Puranik, Pattuparambil R. Rajamohanan, Gangadhar J. Sanjayan|2013|Org.Biomol.Chem.|11|8348|doi:10.1039/C3OB41967C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccydypy
title: CCDC 876391: Experimental Crystal Structure Determination

description: Related Article: Liwen Sun, Xunwen Xiao, Yanjun He, Guannan Wang, Liangjun Shen, Jianghua Fang, Jiangping Yang, Xing Li|2014|Synth.React.Inorg.,Met.-Org.,Nano-Met.Chem.|44|65|doi:10.1080/15533174.2013.768643
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.ccyh0br
title: CCDC 878364: Experimental Crystal Structure Determination

description: Related Article: Pradeep Mathur, Radhe Shyam Ji, Abhinav Raghuvanshi, Mohd. Tauqeer, Shaikh M. Mobin|2017|J.Organomet.Chem.|835|31|doi:10.1016/j.jorganchem.2017.02.036
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccyg8n9
title: CCDC 877661: Experimental Crystal Structure Determination

description: Related Article: Miroslava Martinková, Eva Mezeiová, Jozef Gonda, Dominika Jacková, Kvetoslava Pomikalová|2014|Tetrahedron:Asymm.|25|750|doi:10.1016/j.tetasy.2014.04.002
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.ccyh08p
title: CCDC 878362: Experimental Crystal Structure Determination

description: Related Article: Pradeep Mathur, Radhe Shyam Ji, Abhinav Raghuvanshi, Mohd. Tauqeer, Shaikh M. Mobin|2017|J.Organomet.Chem.|835|31|doi:10.1016/j.jorganchem.2017.02.036
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15156/bio/sh0166430.10fu
title: SH0166430.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.17632/fnmt2tbszr
title: Mendeley Supplemental Figure 5

description: Supplemental Figure 5: Forearm nevus. 2mm in diameter, visualized by digital microscopy alone (A) and by digital microscopy with diascopy (B). Surface scale is removed, and superficial structures are enhanced. Images were captured with NUOTON ABS-506A digital microscope.
DOI: 10.15156/bio/sh0166431.10fu
title: SH0166431.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0166432.10fu
title: SH0166432.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.17632/fnmt2tbszr.1
title: Mendeley Supplemental Figure 5

description: Supplemental Figure 5: Forearm nevus. 2mm in diameter, visualized by digital microscopy alone (A) and by digital microscopy with diascopy (B). Surface scale is removed, and superficial structures are enhanced. Images were captured with NUOTON ABS-506A digital microscope.
DOI: 10.15156/bio/sh0166433.10fu
title: SH0166433.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0166434.10fu
title: SH0166434.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.17632/3jddhy2f6s
title: Phishing URL dataset

description: This is the phishing URL dataset developed for the research titled "A multi-branch hybrid architecture of transformer, CNN, and a deep feed-forward network with MoE for phishing URL detection". It consists of total of 149,726 URLs, of which 94,919 were legitimate, and 54,807 were phishing URLs. The dataset was developed using the Common Crawl (CC-MAIN-2024-33) and Phishtank phishing URL list. The dataset can be used anyone interested in conducting research or developing machine learning based model for phishing detection.
DOI: 10.15156/bio/sh0166435.10fu
title: SH0166435.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.17632/3jddhy2f6s.1
title: Phishing URL dataset

description: This is the phishing URL dataset developed for the research titled "A multi-branch hybrid architecture of transformer, CNN, and a deep feed-forward network with MoE for phishing URL detection". It consists of total of 149,726 URLs, of which 94,919 were legitimate, and 54,807 were phishing URLs. The dataset was developed using the Common Crawl (CC-MAIN-2024-33) and Phishtank phishing URL list. The dataset can be used anyone interested in conducting research or developing machine learning based model for phishing detection.
DOI: 10.5281/zenodo.17874536
title: A Multidisciplinary Roadmap for an Oral Therapeutic to Neutralize Uremic Toxins in Chronic Kidney Disease

description: Background: Chronic Kidney Disease (CKD) represents a profound global health challenge, affecting approximately 843 million individuals worldwide, with end-stage renal disease (ESRD) requiring dialysis in 3.9 million cases (GBD 2021) \cite{1}. The insidious accumulation of cytotoxic protein-bound uremic toxins (PBUTs) drives progressive renal deterioration and multisystemic comorbidities, while established renal replacement therapies like hemodialysis remain invasive, resource-constrained, and burdensome, highlighting unmet needs such as access disparities in low-income countries (WHO 2023) \cite{33}.Methods: This manuscript delineates a comprehensive translational framework for a pioneering oral therapeutic paradigm engineered to neutralize PBUTs via high-affinity competitive binding and augmented clearance mechanisms, potentially offering a viable alternative to dialysis. Harnessing AI-guided medicinal chemistry, advanced nanotechnology, and systems pharmacology, we propose a multi-component nanoparticle-encapsulated formulation to surmount gastrointestinal barriers and achieve targeted bioavailability.Results (Conceptual): Predictive modeling suggests a potential 40-60% reduction in PBUT levels based on rodent models, with enhanced eGFR preservation and mitigation of oxidative stress, supported by Monte Carlo sensitivity analyses demonstrating model robustness.Conclusions: This approach promises a paradigm-shifting, non-invasive, efficacious, and economically viable alternative to dialysis, poised to improve patient-centric outcomes including quality-adjusted life years (QALYs) and healthcare equity, with a call for collaborative preclinical validation.Word count: 350.Keywords: Chronic Kidney Disease, Protein-Bound Uremic Toxins, Competitive Displacement Neutralization, Oral Nanotherapeutics, AI-Optimized Medicinal Chemistry, Systems Pharmacology, Translational Roadmap, Kidney-Gut Axis, Enterohepatic Circulation, Non-Dialytic Clearance.
DOI: 10.5281/zenodo.18196603
title: A Multidisciplinary Roadmap for an Oral Therapeutic to Neutralize Uremic Toxins in Chronic Kidney Disease

description: Background: Chronic Kidney Disease (CKD) represents a profound global health challenge, affecting approximately 843 million individuals worldwide, with end-stage renal disease (ESRD) requiring dialysis in 3.9 million cases (GBD 2021) \cite{1}. The insidious accumulation of cytotoxic protein-bound uremic toxins (PBUTs) drives progressive renal deterioration and multisystemic comorbidities, while established renal replacement therapies like hemodialysis remain invasive, resource-constrained, and burdensome, highlighting unmet needs such as access disparities in low-income countries (WHO 2023) \cite{33}.Methods: This manuscript delineates a comprehensive translational framework for a pioneering oral therapeutic paradigm engineered to neutralize PBUTs via high-affinity competitive binding and augmented clearance mechanisms, potentially offering a viable alternative to dialysis. Harnessing AI-guided medicinal chemistry, advanced nanotechnology, and systems pharmacology, we propose a multi-component nanoparticle-encapsulated formulation to surmount gastrointestinal barriers and achieve targeted bioavailability.Results (Conceptual): Predictive modeling suggests a potential 40-60% reduction in PBUT levels based on rodent models, with enhanced eGFR preservation and mitigation of oxidative stress, supported by Monte Carlo sensitivity analyses demonstrating model robustness.Conclusions: This approach promises a paradigm-shifting, non-invasive, efficacious, and economically viable alternative to dialysis, poised to improve patient-centric outcomes including quality-adjusted life years (QALYs) and healthcare equity, with a call for collaborative preclinical validation.Word count: 350.Keywords: Chronic Kidney Disease, Protein-Bound Uremic Toxins, Competitive Displacement Neutralization, Oral Nanotherapeutics, AI-Optimized Medicinal Chemistry, Systems Pharmacology, Translational Roadmap, Kidney-Gut Axis, Enterohepatic Circulation, Non-Dialytic Clearance.
DOI: 10.15156/bio/sh0166436.10fu
title: SH0166436.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.