Pub Date : 2024-01-01Epub Date: 2024-11-01DOI: 10.21105/joss.06586
Jonathan B Martin, Heng Sun, Madison Albert, Kevin M Johnson, William A Grissom
{"title":"PulPy: A Python Toolkit for MRI RF and Gradient Pulse Design.","authors":"Jonathan B Martin, Heng Sun, Madison Albert, Kevin M Johnson, William A Grissom","doi":"10.21105/joss.06586","DOIUrl":"https://doi.org/10.21105/joss.06586","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"9 103","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12381754/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144984036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-01Epub Date: 2024-09-26DOI: 10.21105/joss.06934
Zhiyi Wu, David L Dotson, Irfan Alibay, Bryce K Allen, Mohammad Soroush Barhaghi, Jérôme Hénin, Thomas T Joseph, Ian M Kenney, Hyungro Lee, Haoxi Li, Victoria Lim, Shuai Liu, Domenico Marson, Pascal T Merz, Alexander Schlaich, David Mobley, Michael R Shirts, Oliver Beckstein
alchemlyb is an open-source Python software package for the analysis of alchemical free energy calculations, an important method in computational chemistry and biology, most notably in the field of drug discovery (Merz et al., 2010). Its functionality contains individual composable building blocks for all aspects of a full typical free energy analysis workflow, starting with the extraction of raw data from the output of diverse molecular simulation packages, moving on to data preprocessing tasks such as decorrelation of time series, using various estimators to derive free energy estimates from simulation samples, and finally providing quality analysis tools for data convergence checking and visualization. alchemlyb also contains high-level end-to-end workflows that combine multiple building blocks into a user-friendly analysis pipeline from the initial data input stage to the final results. This workflow functionality enhances accessibility by enabling researchers from diverse scientific backgrounds, and not solely computational chemistry specialists, to use alchemlyb effectively.
alchemlyb是一个开源的Python软件包，用于分析炼金术自由能计算，这是计算化学和生物学中重要的方法，尤其是在药物发现领域（Merz et al., 2010）。它的功能包含单个可组合的构建块，用于完整典型的自由能分析工作流程的各个方面，从从各种分子模拟包的输出中提取原始数据开始，移动到数据预处理任务，如时间序列的去相关，使用各种估计器从模拟样本中获得自由能估计，最后提供用于数据收敛检查和可视化的质量分析工具。Alchemlyb还包含高级的端到端工作流，它将多个构建块组合成一个用户友好的分析管道，从初始数据输入阶段到最终结果。该工作流功能通过使来自不同科学背景的研究人员（而不仅仅是计算化学专家）能够有效地使用alchemlyb，从而增强了可访问性。
{"title":"alchemlyb: the simple alchemistry library.","authors":"Zhiyi Wu, David L Dotson, Irfan Alibay, Bryce K Allen, Mohammad Soroush Barhaghi, Jérôme Hénin, Thomas T Joseph, Ian M Kenney, Hyungro Lee, Haoxi Li, Victoria Lim, Shuai Liu, Domenico Marson, Pascal T Merz, Alexander Schlaich, David Mobley, Michael R Shirts, Oliver Beckstein","doi":"10.21105/joss.06934","DOIUrl":"10.21105/joss.06934","url":null,"abstract":"<p><p><i>alchemlyb</i> is an open-source Python software package for the analysis of alchemical free energy calculations, an important method in computational chemistry and biology, most notably in the field of drug discovery (Merz et al., 2010). Its functionality contains individual composable building blocks for all aspects of a full typical free energy analysis workflow, starting with the extraction of raw data from the output of diverse molecular simulation packages, moving on to data preprocessing tasks such as decorrelation of time series, using various estimators to derive free energy estimates from simulation samples, and finally providing quality analysis tools for data convergence checking and visualization. <i>alchemlyb</i> also contains high-level end-to-end workflows that combine multiple building blocks into a user-friendly analysis pipeline from the initial data input stage to the final results. This workflow functionality enhances accessibility by enabling researchers from diverse scientific backgrounds, and not solely computational chemistry specialists, to use <i>alchemlyb</i> effectively.</p>","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"9 101","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12352497/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144877658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-01Epub Date: 2024-12-10DOI: 10.21105/joss.07316
Deron Smith, Michael Cyterski, John M Johnston, Kurt Wolfe, Rajbir Parmar
{"title":"ESAT: Environmental Source Apportionment Toolkit Python package.","authors":"Deron Smith, Michael Cyterski, John M Johnston, Kurt Wolfe, Rajbir Parmar","doi":"10.21105/joss.07316","DOIUrl":"10.21105/joss.07316","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"9 104","pages":"7316"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12180922/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144478337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-01Epub Date: 2024-05-29DOI: 10.21105/joss.06604
Ajit J Nirmal, Peter K Sorger
Multiplexed imaging data are revolutionizing our understanding of the composition and organization of tissues and tumors ("Catching up with Multiplexed Tissue Imaging," 2022). A critical aspect of such "tissue profiling" is quantifying the spatial relationships among cells at different scales from the interaction of neighboring cells to recurrent communities of cells of multiple types. This often involves statistical analysis of 107 or more cells in which up to 100 biomolecules (commonly proteins) have been measured. While software tools currently cater to the analysis of spatial transcriptomics data (Liu et al., 2022), there remains a need for toolkits explicitly tailored to the complexities of multiplexed imaging data including the need to seamlessly integrate image visualization with data analysis and exploration. We introduce SCIMAP, a Python package specifically crafted to address these challenges. With SCIMAP, users can efficiently preprocess, analyze, and visualize large datasets, facilitating the exploration of spatial relationships and their statistical significance. SCIMAP's modular design enables the integration of new algorithms, enhancing its capabilities for spatial analysis.
{"title":"SCIMAP: A Python Toolkit for Integrated Spatial Analysis of Multiplexed Imaging Data.","authors":"Ajit J Nirmal, Peter K Sorger","doi":"10.21105/joss.06604","DOIUrl":"10.21105/joss.06604","url":null,"abstract":"<p><p>Multiplexed imaging data are revolutionizing our understanding of the composition and organization of tissues and tumors (\"Catching up with Multiplexed Tissue Imaging,\" 2022). A critical aspect of such \"tissue profiling\" is quantifying the spatial relationships among cells at different scales from the interaction of neighboring cells to recurrent communities of cells of multiple types. This often involves statistical analysis of 10<sup>7</sup> or more cells in which up to 100 biomolecules (commonly proteins) have been measured. While software tools currently cater to the analysis of spatial transcriptomics data (Liu et al., 2022), there remains a need for toolkits explicitly tailored to the complexities of multiplexed imaging data including the need to seamlessly integrate image visualization with data analysis and exploration. We introduce SCIMAP, a Python package specifically crafted to address these challenges. With SCIMAP, users can efficiently preprocess, analyze, and visualize large datasets, facilitating the exploration of spatial relationships and their statistical significance. SCIMAP's modular design enables the integration of new algorithms, enhancing its capabilities for spatial analysis.</p>","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"9 97","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11173324/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141319392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-01Epub Date: 2024-08-23DOI: 10.21105/joss.06067
Anthony Galassi, Martin Norgaard, Adam G Thomas, Gabriel Gonzalez-Escamilla, Claus Svarer, Chris Rorden, Granville J Matheson, Gitte M Knudsen, Robert B Innis, Melanie Ganz, Cyrus Eierud, Murat Bilgel, Cyril Pernet
{"title":"PET2BIDS: a library for converting Positron Emission Tomography data to BIDS.","authors":"Anthony Galassi, Martin Norgaard, Adam G Thomas, Gabriel Gonzalez-Escamilla, Claus Svarer, Chris Rorden, Granville J Matheson, Gitte M Knudsen, Robert B Innis, Melanie Ganz, Cyrus Eierud, Murat Bilgel, Cyril Pernet","doi":"10.21105/joss.06067","DOIUrl":"10.21105/joss.06067","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"9 100","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11414599/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142304913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"NEMSEER: A Python package for downloading and handling\u0000historical National Electricity Market forecast data produced by the\u0000Australian Energy Market Operator","authors":"A. Prakash, A. Bruce, I. MacGill","doi":"10.21105/joss.05883","DOIUrl":"https://doi.org/10.21105/joss.05883","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"11 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138585852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"ER-Evaluation: End-to-End Evaluation of Entity Resolution Systems","authors":"Olivier Binette, Jerome P. Reiter","doi":"10.21105/joss.05619","DOIUrl":"https://doi.org/10.21105/joss.05619","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"53 23","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135041597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"MAHOS: Measurement Automation Handling and Orchestration System","authors":"Kosuke Tahara","doi":"10.21105/joss.05938","DOIUrl":"https://doi.org/10.21105/joss.05938","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"54 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135041592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using the tidyverse with terra objects: the tidyterra package","authors":"Diego Hernangómez","doi":"10.21105/joss.05751","DOIUrl":"https://doi.org/10.21105/joss.05751","url":null,"abstract":"","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":"123 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135136743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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