التفاصيل البيبلوغرافية
| العنوان: |
Master regulator analysis workflow. |
| المؤلفون: |
Jason W. Hoskins (11726336), Charles C. Chung (3074544), Aidan O’Brien (11726339), Jun Zhong (236780), Katelyn Connelly (11726342), Irene Collins (11726345), Jianxin Shi (90453), Laufey T. Amundadottir (3213816) |
| سنة النشر: |
2021 |
| المجموعة: |
Smithsonian Institution: Digital Repository |
| مصطلحات موضوعية: |
Biochemistry, Cell Biology, Genetics, Molecular Biology, Biotechnology, Developmental Biology, Cancer, Infectious Diseases, Computational Biology, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, wide association study, regulators whose activities, phenotypic master regulators, div >< p, detect activity qtls, 35 bmi mr, target network interactions, ephb2 cis <, gwas signal may, ephb2 <, cis <, different regulators, phenotypic mrs, gwas signal, bmi mrs, >- qtls, target overlap, target genes, trans < |
| الوصف: |
First, test cross-validation error for random forest models with increasing numbers of regulators to determine a parsimonious number of regulators sufficient to minimize prediction error. Next, identify the most important regulators as measured by the percent increase in the mean square error (MSE) upon permutation of the regulator in all trees of the forest. Finally, train the final random forest model with the determined number of top regulators by importance and test the model in the test set and validation set. (PDF) |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
unknown |
| العلاقة: |
https://figshare.com/articles/journal_contribution/Master_regulator_analysis_workflow_/17045261Test |
| DOI: |
10.1371/journal.pcbi.1009563.s001 |
| الإتاحة: |
https://doi.org/10.1371/journal.pcbi.1009563.s001Test |
| حقوق: |
CC BY 4.0 |
| رقم الانضمام: |
edsbas.8930A944 |
| قاعدة البيانات: |
BASE |
