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Zenodo
2024
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| Online Access: | https://doi.org/10.5281/zenodo.14955109 |
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| author | Madawalagama, Erandi Prabashani |
| author_facet | Madawalagama, Erandi Prabashani |
| contents | <p><span><span>AlphaFold2, a deep neural network developed by Google </span><span>DeepMind</span><span>, revolutionized structural biology following its groundbreaking performance at the 2020 Critical Assessment of Structure Prediction (CASP) competition, where it achieved unprecedented near-experimental accuracy, significantly outperforming other computational models. This paper critically reviews AlphaFold2’s phased integration into protein science, evaluating its impact on three-dimensional protein structure prediction, its feasibility, and positioning within Gartner's Hype Cycle. Additionally, this review explores how AlphaFold2 accelerated artificial intelligence (AI)-driven protein structure prediction and highlights the potential of deep learning in scientific research. Finally, the future role of AlphaFold2 and its reception within the scientific community are considered.</span></span><span> </span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_14955109 |
| institution | Zenodo |
| language | |
| publishDate | 2024 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Adaptation of Google DeepMind AI AlphaFold2 in Single Protein 3D Structure Prediction: A Critical Review Madawalagama, Erandi Prabashani <p><span><span>AlphaFold2, a deep neural network developed by Google </span><span>DeepMind</span><span>, revolutionized structural biology following its groundbreaking performance at the 2020 Critical Assessment of Structure Prediction (CASP) competition, where it achieved unprecedented near-experimental accuracy, significantly outperforming other computational models. This paper critically reviews AlphaFold2’s phased integration into protein science, evaluating its impact on three-dimensional protein structure prediction, its feasibility, and positioning within Gartner's Hype Cycle. Additionally, this review explores how AlphaFold2 accelerated artificial intelligence (AI)-driven protein structure prediction and highlights the potential of deep learning in scientific research. Finally, the future role of AlphaFold2 and its reception within the scientific community are considered.</span></span><span> </span></p> |
| title | Adaptation of Google DeepMind AI AlphaFold2 in Single Protein 3D Structure Prediction: A Critical Review |
| url | https://doi.org/10.5281/zenodo.14955109 |