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Moving Average-Based Multitasking In Silico Classification Modeling: Where Do We Stand and What Is Next?
Conventional in silico modeling is often viewed as ‘one-target’ or ‘single-task’ computer-aided modeling since it mainly relies on forecasting an endpoint of interest from similar input data. Multitasking or multitarget in silico modeling, in contrast, embraces a set of computational techniques that...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9099502/ https://www.ncbi.nlm.nih.gov/pubmed/35563327 http://dx.doi.org/10.3390/ijms23094937 |
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author | Halder, Amit Kumar Moura, Ana S. Cordeiro, Maria Natália D. S. |
author_facet | Halder, Amit Kumar Moura, Ana S. Cordeiro, Maria Natália D. S. |
author_sort | Halder, Amit Kumar |
collection | PubMed |
description | Conventional in silico modeling is often viewed as ‘one-target’ or ‘single-task’ computer-aided modeling since it mainly relies on forecasting an endpoint of interest from similar input data. Multitasking or multitarget in silico modeling, in contrast, embraces a set of computational techniques that efficiently integrate multiple types of input data for setting up unique in silico models able to predict the outcome(s) relating to various experimental and/or theoretical conditions. The latter, specifically, based upon the Box–Jenkins moving average approach, has been applied in the last decade to several research fields including drug and materials design, environmental sciences, and nanotechnology. The present review discusses the current status of multitasking computer-aided modeling efforts, meanwhile describing both the existing challenges and future opportunities of its underlying techniques. Some important applications are also discussed to exemplify the ability of multitasking modeling in deriving holistic and reliable in silico classification-based models as well as in designing new chemical entities, either through fragment-based design or virtual screening. Focus will also be given to some software recently developed to automate and accelerate such types of modeling. Overall, this review may serve as a guideline for researchers to grasp the scope of multitasking computer-aided modeling as a promising in silico tool. |
format | Online Article Text |
id | pubmed-9099502 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90995022022-05-14 Moving Average-Based Multitasking In Silico Classification Modeling: Where Do We Stand and What Is Next? Halder, Amit Kumar Moura, Ana S. Cordeiro, Maria Natália D. S. Int J Mol Sci Review Conventional in silico modeling is often viewed as ‘one-target’ or ‘single-task’ computer-aided modeling since it mainly relies on forecasting an endpoint of interest from similar input data. Multitasking or multitarget in silico modeling, in contrast, embraces a set of computational techniques that efficiently integrate multiple types of input data for setting up unique in silico models able to predict the outcome(s) relating to various experimental and/or theoretical conditions. The latter, specifically, based upon the Box–Jenkins moving average approach, has been applied in the last decade to several research fields including drug and materials design, environmental sciences, and nanotechnology. The present review discusses the current status of multitasking computer-aided modeling efforts, meanwhile describing both the existing challenges and future opportunities of its underlying techniques. Some important applications are also discussed to exemplify the ability of multitasking modeling in deriving holistic and reliable in silico classification-based models as well as in designing new chemical entities, either through fragment-based design or virtual screening. Focus will also be given to some software recently developed to automate and accelerate such types of modeling. Overall, this review may serve as a guideline for researchers to grasp the scope of multitasking computer-aided modeling as a promising in silico tool. MDPI 2022-04-29 /pmc/articles/PMC9099502/ /pubmed/35563327 http://dx.doi.org/10.3390/ijms23094937 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Halder, Amit Kumar Moura, Ana S. Cordeiro, Maria Natália D. S. Moving Average-Based Multitasking In Silico Classification Modeling: Where Do We Stand and What Is Next? |
title | Moving Average-Based Multitasking In Silico Classification Modeling: Where Do We Stand and What Is Next? |
title_full | Moving Average-Based Multitasking In Silico Classification Modeling: Where Do We Stand and What Is Next? |
title_fullStr | Moving Average-Based Multitasking In Silico Classification Modeling: Where Do We Stand and What Is Next? |
title_full_unstemmed | Moving Average-Based Multitasking In Silico Classification Modeling: Where Do We Stand and What Is Next? |
title_short | Moving Average-Based Multitasking In Silico Classification Modeling: Where Do We Stand and What Is Next? |
title_sort | moving average-based multitasking in silico classification modeling: where do we stand and what is next? |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9099502/ https://www.ncbi.nlm.nih.gov/pubmed/35563327 http://dx.doi.org/10.3390/ijms23094937 |
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