Fernanda I. Saldivar-González*, Diana L. Prado-Romero, Raziel Cedillo-González, Ana L. Chávez-Hernández, Juan F. Avellaneda-Tamayo, Alejandro Gómez-García, Luis Juárez-Rivera and José L. Medina-Franco*,
{"title":"使用 Python 编程检索和分析化学数据的西班牙化学信息学 GitBook","authors":"Fernanda I. Saldivar-González*, Diana L. Prado-Romero, Raziel Cedillo-González, Ana L. Chávez-Hernández, Juan F. Avellaneda-Tamayo, Alejandro Gómez-García, Luis Juárez-Rivera and José L. Medina-Franco*, ","doi":"10.1021/acs.jchemed.4c00041","DOIUrl":null,"url":null,"abstract":"<p >Searching, retrieving, and analyzing chemical information are among the main tasks faced by students and professionals in chemistry-related scientific disciplines. Currently, freely available modules developed in programming languages, such as Python, allow efficient data management and facilitate the obtaining of information and knowledge from the data. This article describes an electronic handbook generated on the GitBook platform to introduce the Python programming language and the analysis, computational representation, and visualization of chemical data. This manual explores the most common molecular representations of low molecular weight organic compounds and their applications in various contexts. It also illustrates the acquisition of chemical data from large public molecular databases such as ChEMBL and PubChem and the analysis and visualization of chemical information using concepts such as chemical space. The GitBook is freely available (https://difacquim.gitbook.io/quimioinformatica/) and is expected to foster open science and facilitate learning for chemistry students at the undergraduate and graduate levels, as well as professionals interested in chemical data analysis and visualization.</p>","PeriodicalId":43,"journal":{"name":"Journal of Chemical Education","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Spanish Chemoinformatics GitBook for Chemical Data Retrieval and Analysis Using Python Programming\",\"authors\":\"Fernanda I. Saldivar-González*, Diana L. Prado-Romero, Raziel Cedillo-González, Ana L. Chávez-Hernández, Juan F. Avellaneda-Tamayo, Alejandro Gómez-García, Luis Juárez-Rivera and José L. Medina-Franco*, \",\"doi\":\"10.1021/acs.jchemed.4c00041\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >Searching, retrieving, and analyzing chemical information are among the main tasks faced by students and professionals in chemistry-related scientific disciplines. Currently, freely available modules developed in programming languages, such as Python, allow efficient data management and facilitate the obtaining of information and knowledge from the data. This article describes an electronic handbook generated on the GitBook platform to introduce the Python programming language and the analysis, computational representation, and visualization of chemical data. This manual explores the most common molecular representations of low molecular weight organic compounds and their applications in various contexts. It also illustrates the acquisition of chemical data from large public molecular databases such as ChEMBL and PubChem and the analysis and visualization of chemical information using concepts such as chemical space. The GitBook is freely available (https://difacquim.gitbook.io/quimioinformatica/) and is expected to foster open science and facilitate learning for chemistry students at the undergraduate and graduate levels, as well as professionals interested in chemical data analysis and visualization.</p>\",\"PeriodicalId\":43,\"journal\":{\"name\":\"Journal of Chemical Education\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Chemical Education\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acs.jchemed.4c00041\",\"RegionNum\":3,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Education","FirstCategoryId":"92","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.jchemed.4c00041","RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
A Spanish Chemoinformatics GitBook for Chemical Data Retrieval and Analysis Using Python Programming
Searching, retrieving, and analyzing chemical information are among the main tasks faced by students and professionals in chemistry-related scientific disciplines. Currently, freely available modules developed in programming languages, such as Python, allow efficient data management and facilitate the obtaining of information and knowledge from the data. This article describes an electronic handbook generated on the GitBook platform to introduce the Python programming language and the analysis, computational representation, and visualization of chemical data. This manual explores the most common molecular representations of low molecular weight organic compounds and their applications in various contexts. It also illustrates the acquisition of chemical data from large public molecular databases such as ChEMBL and PubChem and the analysis and visualization of chemical information using concepts such as chemical space. The GitBook is freely available (https://difacquim.gitbook.io/quimioinformatica/) and is expected to foster open science and facilitate learning for chemistry students at the undergraduate and graduate levels, as well as professionals interested in chemical data analysis and visualization.
期刊介绍:
The Journal of Chemical Education is the official journal of the Division of Chemical Education of the American Chemical Society, co-published with the American Chemical Society Publications Division. Launched in 1924, the Journal of Chemical Education is the world’s premier chemical education journal. The Journal publishes peer-reviewed articles and related information as a resource to those in the field of chemical education and to those institutions that serve them. JCE typically addresses chemical content, activities, laboratory experiments, instructional methods, and pedagogies. The Journal serves as a means of communication among people across the world who are interested in the teaching and learning of chemistry. This includes instructors of chemistry from middle school through graduate school, professional staff who support these teaching activities, as well as some scientists in commerce, industry, and government.