Quantitative Framework for Bench-to-Bedside Cancer Research
Bioscience is an interdisciplinary venture. Driven by a quantum shift in the volume of high throughput data and in ready availability of data-intensive technologies, mathematical and quantitative approaches have become increasingly common in bioscience. For instance, a recent shift towards a quantit...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-10-01
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| Series: | Cancers |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-6694/14/21/5254 |
| _version_ | 1797468829465444352 |
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| author | Aubhishek Zaman Trever G. Bivona |
| author_facet | Aubhishek Zaman Trever G. Bivona |
| author_sort | Aubhishek Zaman |
| collection | DOAJ |
| description | Bioscience is an interdisciplinary venture. Driven by a quantum shift in the volume of high throughput data and in ready availability of data-intensive technologies, mathematical and quantitative approaches have become increasingly common in bioscience. For instance, a recent shift towards a quantitative description of cells and phenotypes, which is supplanting conventional qualitative descriptions, has generated immense promise and opportunities in the field of bench-to-bedside cancer OMICS, chemical biology and pharmacology. Nevertheless, like any burgeoning field, there remains a lack of shared and standardized framework for quantitative cancer research. Here, in the context of cancer, we present a basic framework and guidelines for bench-to-bedside quantitative research and therapy. We outline some of the basic concepts and their parallel use cases for chemical–protein interactions. Along with several recommendations for assay setup and conditions, we also catalog applications of these quantitative techniques in some of the most widespread discovery pipeline and analytical methods in the field. We believe adherence to these guidelines will improve experimental design, reduce variabilities and standardize quantitative datasets. |
| first_indexed | 2024-03-09T19:12:55Z |
| format | Article |
| id | doaj.art-104304f5f30d47e1bd7f1b259ac180f2 |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-09T19:12:55Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-104304f5f30d47e1bd7f1b259ac180f22023-11-24T04:01:28ZengMDPI AGCancers2072-66942022-10-011421525410.3390/cancers14215254Quantitative Framework for Bench-to-Bedside Cancer ResearchAubhishek Zaman0Trever G. Bivona1Department of Medicine, University of California, San Francisco, CA 94158, USADepartment of Medicine, University of California, San Francisco, CA 94158, USABioscience is an interdisciplinary venture. Driven by a quantum shift in the volume of high throughput data and in ready availability of data-intensive technologies, mathematical and quantitative approaches have become increasingly common in bioscience. For instance, a recent shift towards a quantitative description of cells and phenotypes, which is supplanting conventional qualitative descriptions, has generated immense promise and opportunities in the field of bench-to-bedside cancer OMICS, chemical biology and pharmacology. Nevertheless, like any burgeoning field, there remains a lack of shared and standardized framework for quantitative cancer research. Here, in the context of cancer, we present a basic framework and guidelines for bench-to-bedside quantitative research and therapy. We outline some of the basic concepts and their parallel use cases for chemical–protein interactions. Along with several recommendations for assay setup and conditions, we also catalog applications of these quantitative techniques in some of the most widespread discovery pipeline and analytical methods in the field. We believe adherence to these guidelines will improve experimental design, reduce variabilities and standardize quantitative datasets.https://www.mdpi.com/2072-6694/14/21/5254quantitative biologychemical biologybench-to-bedsideOMICSIC50high throughput screen (HTS) |
| spellingShingle | Aubhishek Zaman Trever G. Bivona Quantitative Framework for Bench-to-Bedside Cancer Research Cancers quantitative biology chemical biology bench-to-bedside OMICS IC50 high throughput screen (HTS) |
| title | Quantitative Framework for Bench-to-Bedside Cancer Research |
| title_full | Quantitative Framework for Bench-to-Bedside Cancer Research |
| title_fullStr | Quantitative Framework for Bench-to-Bedside Cancer Research |
| title_full_unstemmed | Quantitative Framework for Bench-to-Bedside Cancer Research |
| title_short | Quantitative Framework for Bench-to-Bedside Cancer Research |
| title_sort | quantitative framework for bench to bedside cancer research |
| topic | quantitative biology chemical biology bench-to-bedside OMICS IC50 high throughput screen (HTS) |
| url | https://www.mdpi.com/2072-6694/14/21/5254 |
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