Building bioinformatics web applications with Streamlit

Chanin Nantasenamat; Avratanu Biswas; J. M. Nápoles-Duarte; Mitchell I. Parker; Roland L. Dunbrack

doi:10.1016/B978-0-443-18638-7.00001-3

Building bioinformatics web applications with Streamlit

Chanin Nantasenamat, Avratanu Biswas, J. M. Nápoles-Duarte, Mitchell I. Parker, Roland L. Dunbrack

Cancer Signaling and Microenvironment (CSM)

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

6 Scopus citations

Abstract

In recent years, we have witnessed an exponential growth in the generation of data in the biological sciences. To harness such big biological data, computational and machine learning pipelines have become instrumental for exploratory data analysis, predictive modeling, and data-driven decision-making. Open-source web development frameworks like Streamlit enable the scientific community to build and share web applications by using less code, thereby speeding up research and development. This chapter explores the usage of Streamlit for the development of software and tools in the field of bioinformatics. The chapter also highlights and goes into depth on selected use cases.

Original language	English
Title of host publication	Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development
Publisher	Elsevier
Pages	679-699
Number of pages	21
ISBN (Electronic)	9780443186387
ISBN (Print)	9780443186394
DOIs	https://doi.org/10.1016/B978-0-443-18638-7.00001-3
State	Published - Jan 1 2023

Keywords

Bioinformatics
Cheminformatics
Drug discovery
Streamlit
Web applications

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10.1016/B978-0-443-18638-7.00001-3

Cite this

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AU - Biswas, Avratanu

AU - Nápoles-Duarte, J. M.

AU - Parker, Mitchell I.

AU - Dunbrack, Roland L.

PY - 2023/1/1

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AB - In recent years, we have witnessed an exponential growth in the generation of data in the biological sciences. To harness such big biological data, computational and machine learning pipelines have become instrumental for exploratory data analysis, predictive modeling, and data-driven decision-making. Open-source web development frameworks like Streamlit enable the scientific community to build and share web applications by using less code, thereby speeding up research and development. This chapter explores the usage of Streamlit for the development of software and tools in the field of bioinformatics. The chapter also highlights and goes into depth on selected use cases.

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KW - Cheminformatics

KW - Drug discovery

KW - Streamlit

KW - Web applications

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BT - Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development

PB - Elsevier

ER -

Building bioinformatics web applications with Streamlit

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Keywords

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