239 results on '"A. C. Wiese"'
Search Results
2. A Comparison of Machine Learning Models for Predicting CRISPR/Cas On-target Efficacy.
3. Best-response dynamics, playing sequences, and convergence to equilibrium in random games.
4. EvoDNN - Evolving Weights, Biases, and Activation Functions in a Deep Neural Network.
5. Navitas/Optimus: A Novel Computational Tool for enhanced CRISPR/Cas Genome Editing.
6. Continuous chromatin state feature annotation of the human epigenome.
7. The Frequency of Convergent Games under Best-Response Dynamics.
8. Spectral Properties of Laplacians on Snowflake Domains and Filled Julia Sets.
9. SigTools: exploratory visualization for genomic signals.
10. EvoDNN - An Evolutionary Deep Neural Network with Heterogeneous Activation Functions.
11. EvoNN: a customizable evolutionary neural network with heterogenous activation functions.
12. Numerical integration methods and layout improvements in the context of dynamic RNA visualization
13. RNA Visualization: Relevance and the Current State-of-the-Art Focusing on Pseudoknots.
14. jViz.RNA 4.0-Visualizing pseudoknots and RNA editing employing compressed tree graphs.
15. Diploidy in evolutionary algorithms for dynamic optimization problems : A best-chromosome-wins dominance mechanism
16. pEvoSAT: a novel permutation based genetic algorithm for solving the boolean satisfiability problem.
17. Non-coding RNA gene finding with combined partial covariance models.
18. Improving the Portability and Performance of jViz.RNA - A Dynamic RNA Visualization Software.
19. Secondary structure element voting for RNA gene finding.
20. Combined covariance model for non-coding RNA gene finding.
21. Improving splice-junctions classification employing a novel encoding schema and decision-tree.
22. An exploration of individual RNA structural elements in RNA gene finding.
23. Expanded study of efn2 thermodynamic model performance on RnaPredict, an evolutionary algorithm for RNA folding.
24. A study of RNA secondary structure prediction using different mutation operators.
25. A permutation based simulated annealing algorithm to predict pseudoknotted RNA secondary structures.
26. A study of different annealing schedules in SARNA-predict: A permutation based SA algorithm for RNA folding.
27. Performance prediction for RNA design using parametric and non-parametric regression models.
28. SARNA-ensemble-predict: The effect of different dissimilarity metrics on a novel ensemble-based RNA secondary structure prediction algorithm.
29. rnaDesign: Local search for RNA secondary structure design.
30. RNA pseudoknot prediction via an evolutionary algorithm.
31. Impact of an enhanced thermodynamic model on RnaPredict, an evolutionary algorithm for RNA secondary structure prediction.
32. The Frequency of Convergent Games under Best-Response Dynamics
33. A hybrid clustering/evolutionary algorithm for RNA folding.
34. SARNA-Predict-pk: Predicting RNA secondary structures including pseudoknots.
35. Considering Stem-Loops as Sequence Signals for Finding Ribosomal RNA Genes.
36. Improved Covariance Model Parameter Estimation Using RNA Thermodynamic Properties.
37. SARNA-Predict: A Study of RNA Secondary Structure Prediction Using Different Annealing Schedules.
38. The significance of thermodynamic models in the accuracy improvement of RNA secondary structure prediction using permutation-based simulated annealing.
39. Graph Drawing Tools for Bioinformatics Research: An Overview.
40. jViz.Rna - An Interactive Graphical Tool for Visualizing RNA Secondary Structure Including Pseudoknots.
41. SARNA-Predict: A Simulated Annealing Algorithm for RNA Secondary Structure Prediction.
42. Analysis of Thermodynamic Models and Performance in RnaPredict - An Evolutionary Algorithm for RNA Folding.
43. A Detailed Analysis of Parallel Speedup in P-RnaPredict - An Evolutionary Algorithm for RNA Secondary Structure Prediction.
44. Cholecalciferol 20 000 IU Once Weekly in HIV-Positive Patients with Low Vitamin D Levels: Result from a Cohort Study
45. Algorithms for RNA folding: a comparison of dynamic programming and parallel evolutionary algorithms.
46. Significance of randomness in P-RnaPredict - a parallel evolutionary algorithm for RNA folding.
47. Comparison of dynamic programming and evolutionary algorithms for RNA secondary structure prediction.
48. A parallel evolutionary algorithm for RNA secondary structure prediction using stacking-energies (INN and INN-HB).
49. Using stacking-energies (INN and INN-HB) for improving the accuracy of RNA secondary structure prediction with an evolutionary algorithm - a comparison to known structures.
50. Permutation-based RNA secondary structure prediction via a genetic algorithm.
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