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Kay C. Wiese
Person information
- affiliation: Simon Fraser University, Burnaby, Canada
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2020 – today
- 2023
- [c48]Amirhossein Daneshpajouh, Megan Fowler, Kay C. Wiese:
Navitas/Optimus: A Novel Computational Tool for enhanced CRISPR/Cas Genome Editing. Canadian AI 2023 - [c47]Megan Fowler, Amirhossein Daneshpajouh, Kay C. Wiese:
A Comparison of Machine Learning Models for Predicting CRISPR/Cas On-target Efficacy. CIBCB 2023: 1-8 - 2022
- [j15]Shohre Masoumi, Maxwell W. Libbrecht, Kay C. Wiese
:
SigTools: exploratory visualization for genomic signals. Bioinform. 38(4): 1126-1128 (2022) - [j14]Habib Daneshpajouh
, Bowen Chen, Neda Shokraneh, Shohre Masoumi, Kay C. Wiese
, Maxwell W. Libbrecht
:
Continuous chromatin state feature annotation of the human epigenome. Bioinform. 38(11): 3029-3036 (2022) - [c46]Peiyu Cui, Kay C. Wiese:
EvoDNN - Evolving Weights, Biases, and Activation Functions in a Deep Neural Network. CIBCB 2022: 1-9
2010 – 2019
- 2019
- [c45]Peiyu Cui, Boris Shabash, Kay C. Wiese:
EvoDNN - An Evolutionary Deep Neural Network with Heterogeneous Activation Functions. CEC 2019: 2362-2369 - 2018
- [c44]Boris Shabash, Kay C. Wiese:
EvoNN: a customizable evolutionary neural network with heterogenous activation functions. GECCO (Companion) 2018: 1449-1456 - 2017
- [j13]Boris Shabash, Kay C. Wiese
:
Numerical integration methods and layout improvements in the context of dynamic RNA visualization. BMC Bioinform. 18(1): 282:1-282:18 (2017) - [j12]Boris Shabash
, Kay C. Wiese:
RNA Visualization: Relevance and the Current State-of-the-Art Focusing on Pseudoknots. IEEE ACM Trans. Comput. Biol. Bioinform. 14(3): 696-712 (2017) - 2015
- [j11]Herbert H. Tsang
, Kay C. Wiese:
A permutation based simulated annealing algorithm to predict pseudoknotted RNA secondary structures. Int. J. Bioinform. Res. Appl. 11(5): 375-396 (2015) - [j10]Herbert H. Tsang
, Kay C. Wiese:
A study of different annealing schedules in SARNA-predict: A permutation based SA algorithm for RNA folding. Int. J. Intell. Comput. Cybern. 8(2): 152-171 (2015) - [j9]Boris Shabash, Kay C. Wiese:
Diploidy in evolutionary algorithms for dynamic optimization problems: A best-chromosome-wins dominance mechanism. Int. J. Intell. Comput. Cybern. 8(4): 312-329 (2015) - 2013
- [c43]Boris Shabash, Kay C. Wiese:
pEvoSAT: a novel permutation based genetic algorithm for solving the boolean satisfiability problem. GECCO 2013: 861-868 - 2012
- [c42]Wenbo Jiang, Kay C. Wiese:
Non-coding RNA gene finding with combined partial covariance models. CIBCB 2012: 306-313 - [c41]Boris Shabash, Kay C. Wiese, Edward Glen:
Improving the Portability and Performance of jViz.RNA - A Dynamic RNA Visualization Software. PRIB 2012: 82-93 - 2011
- [c40]Amin Yazdani Salekdeh, Kay C. Wiese:
Improving splice-junctions classification employing a novel encoding schema and decision-tree. IEEE Congress on Evolutionary Computation 2011: 1302-1307 - [c39]Wenbo Jiang, Kay C. Wiese:
Combined covariance model for non-coding RNA gene finding. CIBCB 2011: 22-26 - [c38]Nicholas George Erho, Kay C. Wiese:
Secondary structure element voting for RNA gene finding. CIBCB 2011: 27-34 - 2010
- [j8]Herbert H. Tsang
, Kay C. Wiese:
SARNA-Predict: Accuracy Improvement of RNA Secondary Structure Prediction Using Permutation-Based Simulated Annealing. IEEE ACM Trans. Comput. Biol. Bioinform. 7(4): 727-740 (2010) - [c37]Herbert H. Tsang
, Tiancheng Jiang, Kay C. Wiese, Christian Jacob:
A study of RNA secondary structure prediction using different mutation operators. IEEE Congress on Evolutionary Computation 2010: 1-7 - [c36]Nicholas George Erho, Kay C. Wiese:
An exploration of individual RNA structural elements in RNA gene finding. CIBCB 2010: 1-9 - [c35]Kay C. Wiese, Andrew Hendriks:
Expanded study of efn2 thermodynamic model performance on RnaPredict, an evolutionary algorithm for RNA folding. CIBCB 2010: 1-8
2000 – 2009
- 2009
- [c34]Kay C. Wiese, Andrew Hendriks:
RNA pseudoknot prediction via an evolutionary algorithm. IEEE Congress on Evolutionary Computation 2009: 270-276 - [c33]Kay C. Wiese, Andrew Hendriks:
Impact of an enhanced thermodynamic model on RnaPredict, an evolutionary algorithm for RNA secondary structure prediction. IEEE Congress on Evolutionary Computation 2009: 2892-2899 - [c32]Denny C. Dai, Herbert H. Tsang
, Kay C. Wiese:
rnaDesign: Local search for RNA secondary structure design. CIBCB 2009: 1-7 - [c31]Herbert H. Tsang
, Kay C. Wiese:
SARNA-ensemble-predict: The effect of different dissimilarity metrics on a novel ensemble-based RNA secondary structure prediction algorithm. CIBCB 2009: 8-15 - [c30]Denny C. Dai, Kay C. Wiese:
Performance prediction for RNA design using parametric and non-parametric regression models. CIBCB 2009: 16-23 - 2008
- [j7]Kay C. Wiese, Alain Deschênes, Andrew Hendriks:
RnaPredict-An Evolutionary Algorithm for RNA Secondary Structure Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. 5(1): 25-41 (2008) - [j6]Scott F. Smith, Kay C. Wiese:
Integrating Thermodynamic and Observed-Frequency Data for Non-coding RNA Gene Search. Trans. Comp. Sys. Biology 10: 124-142 (2008) - [c29]Herbert H. Tsang
, Kay C. Wiese:
SARNA-Predict-pk: Predicting RNA secondary structures including pseudoknots. CIBCB 2008: 1-8 - [c28]Kay C. Wiese, Andrew Hendriks:
A hybrid clustering/evolutionary algorithm for RNA folding. CIBCB 2008: 15-21 - [p1]Kirt M. Noël, Kay C. Wiese:
Considering Stem-Loops as Sequence Signals for Finding Ribosomal RNA Genes. Computational Intelligence in Biomedicine and Bioinformatics 2008: 337-357 - 2007
- [j5]Kay C. Wiese:
Society Briefs - Bioinformatics and Bioengineering Technical Committee. IEEE Comput. Intell. Mag. 2(2): 72-73 (2007) - [c27]Scott F. Smith, Kay C. Wiese:
Improved Covariance Model Parameter Estimation Using RNA Thermodynamic Properties. BIONETICS 2007: 185-191 - [c26]Herbert H. Tsang
, Kay C. Wiese:
The significance of thermodynamic models in the accuracy improvement of RNA secondary structure prediction using permutation-based simulated annealing. IEEE Congress on Evolutionary Computation 2007: 3879-3885 - [c25]Herbert H. Tsang, Kay C. Wiese:
SARNA-Predict: A Study of RNA Secondary Structure Prediction Using Different Annealing Schedules. CIBCB 2007: 239-246 - 2006
- [j4]Kay C. Wiese, Andrew Hendriks:
Comparison of P-RnaPredict and mfold - algorithms for RNA secondary structure prediction. Bioinform. 22(8): 934-942 (2006) - [j3]H. Alexander Ebhardt
, Kay C. Wiese, Peter J. Unrau:
Ebbie: automated analysis and storage of small RNA cloning data using a dynamic web server. BMC Bioinform. 7: 185 (2006) - [j2]Kay C. Wiese:
IEEE/CIS Tour de China [Family Corner]. IEEE Comput. Intell. Mag. 1(4): 15-17 (2006) - [c24]Kay C. Wiese, Christina Eicher:
Graph Drawing Tools for Bioinformatics Research: An Overview. CBMS 2006: 653-658 - [c23]Kay C. Wiese, Edward Glen:
jViz.Rna - An Interactive Graphical Tool for Visualizing RNA Secondary Structure Including Pseudoknots. CBMS 2006: 659-664 - [c22]Kay C. Wiese, Andrew Hendriks:
A Detailed Analysis of Parallel Speedup in P-RnaPredict - An Evolutionary Algorithm for RNA Secondary Structure Prediction. IEEE Congress on Evolutionary Computation 2006: 2323-2330 - [c21]Herbert H. Tsang
, Kay C. Wiese:
SARNA-Predict: A Simulated Annealing Algorithm for RNA Secondary Structure Prediction. CIBCB 2006: 1-10 - [c20]Kay C. Wiese, Andrew Hendriks, Alain Deschênes:
Analysis of Thermodynamic Models and Performance in RnaPredict - An Evolutionary Algorithm for RNA Folding. CIBCB 2006: 1-9 - 2005
- [c19]Kay C. Wiese, Andrew Hendriks, Alain Deschênes, Belgacem Ben Youssef:
Significance of randomness in P-RnaPredict - a parallel evolutionary algorithm for RNA folding. Congress on Evolutionary Computation 2005: 467-474 - [c18]Kay C. Wiese, Andrew Hendriks, Jagdeep Poonian:
Algorithms for RNA folding: a comparison of dynamic programming and parallel evolutionary algorithms. Congress on Evolutionary Computation 2005: 475-483 - [c17]Kay C. Wiese, Andrew Hendriks, Alain Deschênes, Belgacem Ben Youssef:
The impact of pseudorandom number quality on P-RnaPredict, a parallel genetic algorithm for RNA secondary structure prediction. GECCO 2005: 479-480 - 2004
- [c16]Alain Deschênes, Kay C. Wiese, Edward Glen:
Comparison of Permutation-Based and Binary Representation in a Genetic Algorithm for RNA Secondary Structure Prediction. Canadian AI 2004: 549-550 - [c15]Andrew Hendriks, Kay C. Wiese, Edward Glen:
Comparison of Parallel and Serial Genetic Algorithms for RNA Secondary Structure Prediction. Canadian AI 2004: 554-555 - [c14]Lenny Tang, Kay C. Wiese, Vive Kumar
:
Genetic Algorithm Based OSPF Network Routing Using LEDA. Canadian AI 2004: 571-572 - [c13]Alain Deschênes, Kay C. Wiese:
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. IEEE Congress on Evolutionary Computation 2004: 598-606 - [c12]Alain Deschênes, Kay C. Wiese, Jagdeep Poonian:
Comparison of dynamic programming and evolutionary algorithms for RNA secondary structure prediction. CIBCB 2004: 214-222 - [c11]Andrew Hendriks, Alain Deschênes, Kay C. Wiese:
A parallel evolutionary algorithm for RNA secondary structure prediction using stacking-energies (INN and INN-HB). CIBCB 2004: 223-230 - [c10]Kirt M. Noël, Kay C. Wiese:
Exploring the Use of Stem-Loop Characteristics for Pinpointing Structural RNA Genes. CSB 2004: 533-534 - 2003
- [c9]Kay C. Wiese, Alain Deschênes, Edward Glen:
Permutation-based RNA secondary structure prediction via a genetic algorithm. IEEE Congress on Evolutionary Computation 2003: 335-342 - [c8]Andrew Hendriks, Kay C. Wiese, Edward Glen, Alain Deschênes:
A distributed genetic algorithm for RNA secondary structure prediction. IEEE Congress on Evolutionary Computation 2003: 343-350 - [c7]Kay C. Wiese, Edward Glen:
RNA Structure as Permutation: A GA Approach Comparing Different Genetic Sequencing Operators. ISMIS 2003: 511-520 - 2002
- [c6]Kay C. Wiese, Edward Glen:
A Permutation Based Genetic Algorithm for RNA Secondary Structure Prediction. HIS 2002: 173-182 - 2001
- [j1]Kay C. Wiese, Scott D. Goodwin:
Keep-Best Reproduction: A Local Family Competition Selection Strategy and the Environment it Flourishes in. Constraints An Int. J. 6(4): 399-422 (2001) - 2000
- [c5]Kay C. Wiese, Scott D. Goodwin, Sivakumar Nagarajan:
ASERC - A Genetic Sequencing Operator for Asymmetric Permutation Problems. AI 2000: 201-213
1990 – 1999
- 1999
- [c4]Kay C. Wiese, Scott D. Goodwin:
Convergence Characteristics of Keep-Best Reproduction. SAC 1999: 312-318 - 1998
- [c3]Kay C. Wiese, Scott D. Goodwin:
The Effect of Genetic Operator Probabilities and Selection Strategies on the Performance of a Genetic Algorithm. Canadian AI 1998: 139-153 - [c2]Kay C. Wiese, Sivakumar Nagarajan, Scott D. Goodwin:
Parallel Genetic Algorithms for Constrained Ordering Problems. FLAIRS 1998: 101-105 - [c1]Kay C. Wiese, Scott D. Goodwin:
Keep-best reproduction: a selection strategy for genetic algorithms. SAC 1998: 343-348
Coauthor Index
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