Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data حسب Andreas Tosstorff (8250999)

الموضوعات:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data حسب Andreas Tosstorff (8250999)

الموضوعات:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data حسب Andreas Tosstorff (8250999)

الموضوعات:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data حسب Andreas Tosstorff (8250999)

الموضوعات:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data حسب Andreas Tosstorff (8250999)

الموضوعات:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data حسب Andreas Tosstorff (8250999)

الموضوعات:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data حسب Andreas Tosstorff (8250999)

الموضوعات:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data حسب Andreas Tosstorff (8250999)

الموضوعات:

Supplemental files to the study "Limitations of Current Machine-Learning Models in Predicting Enzymatic Functions for Uncharacterized Proteins" حسب Valerie de Crecy-Lagard (12823436)

"…Machine-Learning (ML) approaches are enticing, with early successes demonstrating the ability to propagate functional knowledge from experimentally characterized proteins. …"

Quantum Computing and peptide folding حسب Akshay Uttarkar (19699990)

"…Authored by Akshay Uttarkar and Vidya Niranjan, this research harnesses the power of quantum computing to tackle one of the most complex problems in biochemistry: predicting the three-dimensional structures of proteins from their amino acid sequences.</p><p dir="ltr">At its core, the study introduces the Conditional Value at Risk-Variational Quantum Eigensolver (CVaR-VQE) algorithm, a hybrid quantum-classical approach that effectively predicts the lowest energy conformations of peptides. …"

Results from different ML algorithms. حسب Caroline L. Alves (14271413)

Performance of various deep learning models from PyNoetic’s classification module on the Motor Imagery decoding task. حسب Gursimran Singh (575288)

الموضوعات:

Supplemental Tables S1 and S2 for Combining structural modeling and deep learning to calculate the E. coli protein interactome and functional networks حسب Diana Murray (16859046)

"…Biological insights derived from the subnetworks, including the annotation of proteins of unknown function, are discussed in detail. …"

Hist-8000 sequence similarity scores are closer to the ground truth than the corresponding Sum-of-learnt-Trigrams scores. (NW, Hist-8000) and (NW, Hist-SDM12) are both higher than... حسب Frixos Papadopoulos (22001664)

a-c: (a) The nomogram model developed for the prognostic prediction of hub genes from the study. حسب Devi Soorya Narayana Sasikumar (22331743)

الموضوعات:

A) Ranking of models trained on different feature sets across all tested algorithms, sorted by their F1-score. حسب Jose Cleydson F. Silva (8685594)

Selected optimal solutions from the QLNSGA-II algorithm. حسب Zhongfeng Li (3965060)

Isologs, function and residue information of 12 key proteins in MPV replication. حسب Huaichuan Duan (6458477)

Wilcoxon rank sum test results from MWOA and 7 comparison algorithms on CEC2005 functions. حسب Yi-Qiang Xia (20161326)

"…<p>Wilcoxon rank sum test results from MWOA and 7 comparison algorithms on CEC2005 functions.…"

Predicted body weights (kg) as a function of time (age in weeks) obtained from MARS algorithm. حسب Turgay Şengül (12801990)

"…<p>Predicted body weights (kg) as a function of time (age in weeks) obtained from MARS algorithm.…"