Quantitative Structure-Activity Relationships: Linear Regression Modelling and Validation Strategies by Example
AbstractQuantitative structure-activity relationships are mathematical models constructed based on the hypothesis that structure of chemical compounds is related to their biological activity. A linear regression model is often used to estimate and predict the nature of the relationships between a measured activity and some measure or calculated descriptors. Linear regression helps to answer main three questions: does the biological activity depend on structure information; if so, the nature of the relationship is linear; and if yes, how good is the model in prediction of the biological activity of new compounds. This manuscript presents the steps on linear regression analysis moving from theoretical knowledge to an example conducted on sets of endocrine disrupting chemicals.
The journal Biomath is an open access journal. All published articles are immeditely available online and the respective DOI link activated. All articles can be access for free and no reader registration of any sort is required. No fees are charged to authors for article submission or processing. Online publications are funded through volunteer work, donations and grants.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License 4.0 that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).