Teaching Cheminformatics through a Collaborative Intercollegiate Online Chemistry Course (OLCC)

Kim, Sunghwan; Bucholtz, Ehren C.; Briney, Kristin; Cornell, Andrew P.; Cuadros, Jordi; Fulfer, Kristen D.; Gupta, Tanya; Hepler-Smith, Evan; Johnston, Dean H.; Lang, Andrew S. I. D.; Larsen, Delmar S.; Li, Ye; McEwen, Leah; Morsch, Layne A.; Muzyka, Jennifer L.; Belford, Robert E.

doi:10.1021/acs.jchemed.0c01035

Cited by 21 publications

(24 citation statements)

References 49 publications

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“…Small molecule drugs with a negative mean connective score and P < 0.05 were considered statistically significant and had inhibitory effects. The chemical structures of these small molecule compounds were obtained from the PubChem ( https://pubchem.ncbi.nlm.nih.gov ) database [ 29 , 30 , 31 , 32 , 33 ].…”

Section: Methodsmentioning

confidence: 99%

Comprehensive investigation of RNA‐sequencing dataset reveals the hub genes and molecular mechanisms of coronavirus disease 2019 acute respiratory distress syndrome

Deng

Zeng

et al. 2021

IET Systems Biology

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The goal of this study is to reveal the hub genes and molecular mechanisms of the coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS) based on the genome-wide RNA sequencing dataset. The RNA sequencing dataset of COVID-19 ARDS was obtained from GSE163426. A total of 270 differentially expressed genes (DEGs) were identified between COVID-19 ARDS and control group patients. Functional enrichment analysis of DEGs suggests that these DEGs may be involved in the following biological processes: response to cytokine, G-protein coupled receptor activity, ionotropic glutamate receptor signalling pathway and G-protein coupled receptor signalling pathway. By using the weighted correlation network analysis approach to analyse these DEGs, 10 hub DEGs that may play an important role in COVID-19 ARDS were identified. A total of 67 potential COVID-19 ARDS targetted drugs were identified by a complement map analysis. Immune cell infiltration analysis revealed that the levels of T cells CD4 naive, T cells follicular helper, macrophages M1 and eosinophils in COVID-19 ARDS patients were significantly different from those in control group patients. In conclusion, this study identified 10 COVID-19 ARDS-related hub DEGs and numerous potential molecular mechanisms through a comprehensive analysis of the RNA sequencing dataset and also revealed the difference in immune cell infiltration of COVID-19 ARDS. K E Y W O R D S acute respiratory distress syndrome, coronavirus disease 2019, GSE163426, hub genes, molecular mechanism 1 | INTRODUCTION Coronavirus disease 2019 (COVID-19), named by the World Health Organization, refers to pneumonia caused by the 2019 novel coronavirus infection. The International Committee on Classification of Viruses also named this new type of coronavirus 'SARS-CoV-2' (Severe Acute Respiratory Syndrome Coronavirus 2) [1]. At present, there are more than 100 million patients diagnosed with COVID-19 worldwide, and more than 3 million patients have died. There are still 30 million patients with COVID-19. The clinical manifestations of COVID-19-infected pneumonia patients include fever, fatigue, and dry cough, which are its main manifestations [2].Upper respiratory symptoms such as nasal congestion and runny nose are rare, and hypoxia is present [3]. About half of the patients have difficulty breathing more than a week later. In severe cases, it leads to acute respiratory distress syndrome (ARDS), septic shock, metabolic acidosis, and coagulation dysfunction [4,5]. ARDS is also the main cause of death for COVID-19 patients. However, it is still unclear which people are more likely to develop ARDS, and which are the related factors in patients who develop ARDS that lead to death. Therefore, we urgently need a better understanding of COVID-19 ARDS.Wangsheng Deng and Jiaxing Zeng contributed equally to this work.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original ...

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Section: Methodsmentioning

confidence: 99%

Comprehensive investigation of RNA‐sequencing dataset reveals the hub genes and molecular mechanisms of coronavirus disease 2019 acute respiratory distress syndrome

Deng

Zeng

et al. 2021

IET Systems Biology

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“…Another relevant course for cheminformatics was organized by the Committee on Computers in Chemical Education, a part of the American Chemical Society's Division of Chemical Education. 19 Regarding machine learning, the material developed for teaching chemistry students is more scarce. An in-depth discussion of the methodologies for chemical systems can be found elsewhere.…”

Section: ■ Introductionmentioning

confidence: 99%

A Gentle Introduction to Machine Learning for Chemists: An Undergraduate Workshop Using Python Notebooks for Visualization, Data Processing, Analysis, and Modeling

et al. 2021

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Machine learning, a subdomain of artificial intelligence, is a widespread technology that is molding how chemists interact with data. Therefore, it is a relevant skill to incorporate into the toolbox of any chemistry student. This work presents a workshop that introduces machine learning for chemistry students based on a set of Python notebooks and assignments. Python, one of the most popular programming languages, is open source, free to use, and has plenty of learning resources. The workshop is designed for students without previous experience in programming, and it aims for a deeper understanding of the complexity of concepts in programming and machine learning. The examples used correspond to real data from physicochemical characterizations of wine, a content that is of interest for students. The contents of the workshop are introduction to Python, basic statistics, data visualization, and dimension reduction, classification, and regression.

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“…PubChem includes three databases: PubChem Compound (standardized compounds), PubChem Substance (depositor contributed substance information), and PubChem BioAssay (depositor contributed bioactivity information). Together, these PubChem databases provide access to one of the largest programmatically accessible collections of machine-readable chemical information, with millions of small molecules, associated data, and linked literature references available. − Indeed, in a recent report by Kim et al that outlines a collaborative cheminformatics online chemistry course (OLCC), teaching students how to access chemical data from PubChem programmatically was a core component of the course educational content. In the most current cheminformatics OLCC, Jupyter notebooks with Python and R programmatic scripts were used to teach students how to access PubChem data.…”

Section: Introductionmentioning

confidence: 99%

Using NCBI Entrez Direct (EDirect) for Small Molecule Chemical Information Searching in a Unix Terminal

Scalfani

2021

J. Chem. Educ.

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The National Center for Biotechnology Information Entrez Direct (EDirect) software facilitates programmatic access to numerous biomedical, chemical, and literature databases from within a Unix terminal. EDirect has traditionally been used for command line access to NCBI data within the fields of computational biology and bioinformatics. This Article describes how EDirect can be used for programmatic retrieval of small molecule and related chemical information from the PubChem and PubMed databases, useful for the chemical and cheminformatics communities. Several use cases are presented that demonstrate using EDirect in applications such as retrieving small molecule chemical property information, compound bibliometric data, and literature references. In addition, more advanced use cases are discussed that demonstrate how to incorporate EDirect searches into reproducible data analysis workflows, for example, with data visualization programs and cheminformatics toolkits. Since EDirect is a collection of command line programs, the syntax to perform programmatic search queries and related operations is simplified and suitable for beginners. This is in contrast to common approaches of programmatic chemical information searching using computational notebooks that may require additional training and computer programming skills. As a result of the more beginner friendly learning curve, EDirect may be particularly useful for chemical information professionals that often teach one time workshops where there is limited time to introduce programming concepts to students. This Article concludes with an example implementation of teaching EDirect and a review of the limitations. Approximately 20 EDirect scripts useful for programmatic small molecule chemical information searching are included in this Article and in the Supporting Information. All EDirect scripts shared have a permissible open source license, and educators are highly encouraged to adapt the scripts and workflows as desired.

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Teaching Cheminformatics through a Collaborative Intercollegiate Online Chemistry Course (OLCC)

Cited by 21 publications

References 49 publications

Comprehensive investigation of RNA‐sequencing dataset reveals the hub genes and molecular mechanisms of coronavirus disease 2019 acute respiratory distress syndrome

Comprehensive investigation of RNA‐sequencing dataset reveals the hub genes and molecular mechanisms of coronavirus disease 2019 acute respiratory distress syndrome

A Gentle Introduction to Machine Learning for Chemists: An Undergraduate Workshop Using Python Notebooks for Visualization, Data Processing, Analysis, and Modeling

Using NCBI Entrez Direct (EDirect) for Small Molecule Chemical Information Searching in a Unix Terminal

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