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1	Material Type: Article	Correction: A quantitative analysis of the impact of explicit incorporation of recency, seasonality and model specialization into fine-grained tourism demand prediction models PloS one, 2023-10, Vol.18 (10), p.e0292825-e0292825 [Peer Reviewed Journal] COPYRIGHT 2023 Public Library of Science ;2023 The PLOS ONE Staff. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2023 The PLOS ONE Staff 2023 The PLOS ONE Staff ;2023 The PLOS ONE Staff. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0292825 ;PMID: 37812602 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
2	Material Type: Article	The citation advantage of linking publications to research data PloS one, 2020-04, Vol.15 (4), p.e0230416-e0230416 [Peer Reviewed Journal] COPYRIGHT 2020 Public Library of Science ;2020 Colavizza et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2020 Colavizza et al 2020 Colavizza et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0230416 ;PMID: 32320428 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
3	Material Type: Article	DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences PLoS computational biology, 2019-06, Vol.15 (6), p.e1007129 [Peer Reviewed Journal] COPYRIGHT 2019 Public Library of Science ;COPYRIGHT 2019 Public Library of Science ;2019 Lee et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2019 Lee et al 2019 Lee et al ;ISSN: 1553-7358 ;ISSN: 1553-734X ;EISSN: 1553-7358 ;DOI: 10.1371/journal.pcbi.1007129 ;PMID: 31199797 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
4	Material Type: Article	Compositional shifts in root-associated bacterial and archaeal microbiota track the plant life cycle in field-grown rice PLoS biology, 2018-02, Vol.16 (2), p.e2003862-e2003862 [Peer Reviewed Journal] 2018 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Edwards JA, Santos-Medellín CM, Liechty ZS, Nguyen B, Lurie E, Eason S, et al. (2018) Compositional shifts in root-associated bacterial and archaeal microbiota track the plant life cycle in field-grown rice. PLoS Biol 16(2): e2003862. https://doi.org/10.1371/journal.pbio.2003862 ;2018 Edwards et al 2018 Edwards et al ;2018 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Edwards JA, Santos-Medellín CM, Liechty ZS, Nguyen B, Lurie E, Eason S, et al. (2018) Compositional shifts in root-associated bacterial and archaeal microbiota track the plant life cycle in field-grown rice. PLoS Biol 16(2): e2003862. https://doi.org/10.1371/journal.pbio.2003862 ;ISSN: 1545-7885 ;ISSN: 1544-9173 ;EISSN: 1545-7885 ;DOI: 10.1371/journal.pbio.2003862 ;PMID: 29474469 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
5	Material Type: Article	Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways PloS one, 2017-09, Vol.12 (9), p.e0184129-e0184129 [Peer Reviewed Journal] COPYRIGHT 2017 Public Library of Science ;COPYRIGHT 2017 Public Library of Science ;2017 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2017 Chen et al 2017 Chen et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0184129 ;PMID: 28873455 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
6	Material Type: Article	Forecasting stock prices with long-short term memory neural network based on attention mechanism PloS one, 2020-01, Vol.15 (1), p.e0227222-e0227222 [Peer Reviewed Journal] COPYRIGHT 2020 Public Library of Science ;COPYRIGHT 2020 Public Library of Science ;2020 Qiu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2020 Qiu et al 2020 Qiu et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0227222 ;PMID: 31899770 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
7	Material Type: Article	Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants PloS one, 2019-05, Vol.14 (5), p.e0213653-e0213653 [Peer Reviewed Journal] COPYRIGHT 2019 Public Library of Science ;COPYRIGHT 2019 Public Library of Science ;2019 Alaa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2019 Alaa et al 2019 Alaa et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0213653 ;PMID: 31091238 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
8	Material Type: Article	Prediction model and risk scores of ICU admission and mortality in COVID-19 PloS one, 2020-07, Vol.15 (7), p.e0236618 [Peer Reviewed Journal] 2020 Zhao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2020 Zhao et al 2020 Zhao et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0236618 ;PMID: 32730358 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
9	Material Type: Article	In silico approach for predicting toxicity of peptides and proteins PloS one, 2013-09, Vol.8 (9), p.e73957 [Peer Reviewed Journal] COPYRIGHT 2013 Public Library of Science ;COPYRIGHT 2013 Public Library of Science ;2013 Gupta et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2013 Gupta et al 2013 Gupta et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0073957 ;PMID: 24058508 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
10	Material Type: Article	A systematic review of machine learning models for predicting outcomes of stroke with structured data PloS one, 2020-06, Vol.15 (6), p.e0234722 [Peer Reviewed Journal] COPYRIGHT 2020 Public Library of Science ;2020 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2020 Wang et al 2020 Wang et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0234722 ;PMID: 32530947 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
11	Material Type: Article	Nature is the best source of anticancer drugs: Indexing natural products for their anticancer bioactivity PloS one, 2017-11, Vol.12 (11), p.e0187925-e0187925 [Peer Reviewed Journal] COPYRIGHT 2017 Public Library of Science ;COPYRIGHT 2017 Public Library of Science ;2017 Rayan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2017 Rayan et al 2017 Rayan et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0187925 ;PMID: 29121120 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
12	Material Type: Article	SoilGrids1km--global soil information based on automated mapping PloS one, 2014-08, Vol.9 (8), p.e105992-e105992 [Peer Reviewed Journal] 2014 Hengl et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2014 Hengl et al 2014 Hengl et al ;Wageningen University & Research ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0105992 ;PMID: 25171179 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
13	Material Type: Article	Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study PLoS medicine, 2017-04, Vol.14 (4), p.e1002277-e1002277 [Peer Reviewed Journal] COPYRIGHT 2017 Public Library of Science ;COPYRIGHT 2017 Public Library of Science ;2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: ten Haaf K, Jeon J, Tammemägi MC, Han SS, Kong CY, Plevritis SK, et al. (2017) Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study. PLoS Med 14(4): e1002277. https://doi.org/10.1371/journal.pmed.1002277 ;2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: ten Haaf K, Jeon J, Tammemägi MC, Han SS, Kong CY, Plevritis SK, et al. (2017) Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study. PLoS Med 14(4): e1002277. https://doi.org/10.1371/journal.pmed.1002277 ;ISSN: 1549-1676 ;ISSN: 1549-1277 ;EISSN: 1549-1676 ;DOI: 10.1371/journal.pmed.1002277 ;PMID: 28376113 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
14	Material Type: Article	Distinct subtypes of polycystic ovary syndrome with novel genetic associations: An unsupervised, phenotypic clustering analysis PLoS medicine, 2020-06, Vol.17 (6), p.e1003132-e1003132 [Peer Reviewed Journal] COPYRIGHT 2020 Public Library of Science ;COPYRIGHT 2020 Public Library of Science ;2020 Dapas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2020 Dapas et al 2020 Dapas et al ;ISSN: 1549-1676 ;ISSN: 1549-1277 ;EISSN: 1549-1676 ;DOI: 10.1371/journal.pmed.1003132 ;PMID: 32574161 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
15	Material Type: Article	Utility of ctDNA in predicting response to neoadjuvant chemoradiotherapy and prognosis assessment in locally advanced rectal cancer: A prospective cohort study PLoS medicine, 2021-08, Vol.18 (8), p.e1003741 [Peer Reviewed Journal] COPYRIGHT 2021 Public Library of Science ;2021 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2021 Wang et al 2021 Wang et al ;ISSN: 1549-1676 ;ISSN: 1549-1277 ;EISSN: 1549-1676 ;DOI: 10.1371/journal.pmed.1003741 ;PMID: 34464382 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
16	Material Type: Article	Apollo: Democratizing genome annotation PLoS computational biology, 2019-02, Vol.15 (2), p.e1006790-e1006790 [Peer Reviewed Journal] COPYRIGHT 2019 Public Library of Science ;COPYRIGHT 2019 Public Library of Science ;2019 Dunn et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2019 Dunn et al 2019 Dunn et al ;ISSN: 1553-7358 ;ISSN: 1553-734X ;EISSN: 1553-7358 ;DOI: 10.1371/journal.pcbi.1006790 ;PMID: 30726205 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
17	Material Type: Article	PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction PLoS computational biology, 2017-03, Vol.13 (3), p.e1005455-e1005455 [Peer Reviewed Journal] COPYRIGHT 2017 Public Library of Science ;COPYRIGHT 2017 Public Library of Science ;2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: You Z-H, Huang Z-A, Zhu Z, Yan G-Y, Li Z-W, Wen Z, et al. (2017) PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction. PLoS Comput Biol 13(3): e1005455. https://doi.org/10.1371/journal.pcbi.1005455 ;2017 You et al 2017 You et al ;2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: You Z-H, Huang Z-A, Zhu Z, Yan G-Y, Li Z-W, Wen Z, et al. (2017) PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction. PLoS Comput Biol 13(3): e1005455. https://doi.org/10.1371/journal.pcbi.1005455 ;ISSN: 1553-7358 ;ISSN: 1553-734X ;EISSN: 1553-7358 ;DOI: 10.1371/journal.pcbi.1005455 ;PMID: 28339468 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
18	Material Type: Article	Development of machine learning models for diagnosis of glaucoma PloS one, 2017-05, Vol.12 (5), p.e0177726 [Peer Reviewed Journal] COPYRIGHT 2017 Public Library of Science ;COPYRIGHT 2017 Public Library of Science ;2017 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2017 Kim et al 2017 Kim et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0177726 ;PMID: 28542342 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
19	Material Type: Article	Machine learning modeling of family wide enzyme-substrate specificity screens PLoS computational biology, 2022-02, Vol.18 (2), p.e1009853-e1009853 [Peer Reviewed Journal] COPYRIGHT 2022 Public Library of Science ;2022 Goldman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 Goldman et al 2022 Goldman et al ;ISSN: 1553-7358 ;ISSN: 1553-734X ;EISSN: 1553-7358 ;DOI: 10.1371/journal.pcbi.1009853 ;PMID: 35143485 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
20	Material Type: Article	Prioritized and predictive intelligence of things enabled waste management model in smart and sustainable environment PloS one, 2022-08, Vol.17 (8), p.e0272383-e0272383 [Peer Reviewed Journal] COPYRIGHT 2022 Public Library of Science ;2022 Mishra et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 Mishra et al 2022 Mishra et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0272383 ;PMID: 35951589 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by