 Connection
Gregg Beckham to Machine Learning
This is a "connection" page, showing publications Gregg Beckham has written about Machine Learning.
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Connection Strength |
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0.865 |
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Komp E, Johansson KE, Gauthier NP, Gado JE, Lindorff-Larsen K, Beckham GT. Accessible, uniform protein property prediction with a scikit-learn based toolset AIDE. Bioinformatics. 2025 Oct 02; 41(10).
Score: 0.614
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Gado JE, Harrison BE, Sandgren M, Ståhlberg J, Beckham GT, Payne CM. Machine learning reveals sequence-function relationships in family 7 glycoside hydrolases. J Biol Chem. 2021 Aug; 297(2):100931.
Score: 0.114
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Gado JE, Beckham GT, Payne CM. Improving Enzyme Optimum Temperature Prediction with Resampling Strategies and Ensemble Learning. J Chem Inf Model. 2020 08 24; 60(8):4098-4107.
Score: 0.107
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Lim HG, Rychel K, Sastry AV, Bentley GJ, Mueller J, Schindel HS, Larsen PE, Laible PD, Guss AM, Niu W, Johnson CW, Beckham GT, Feist AM, Palsson BO. Machine-learning from Pseudomonas putida KT2440 transcriptomes reveals its transcriptional regulatory network. Metab Eng. 2022 07; 72:297-310.
Score: 0.030
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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