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ORCIDGail L. Rosen
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2020 – today
- 2024
[j21]Rohan Chandraghatgi
, Hai-Feng Ji, Gail L. Rosen, Bahrad A. Sokhansanj:
Streamlining Computational Fragment-Based Drug Discovery through Evolutionary Optimization Informed by Ligand-Based Virtual Prescreening. J. Chem. Inf. Model. 64(9): 3826-3840 (2024)- [i1]Hyunwoo Yoo, Bahrad A. Sokhansanj, James R. Brown, Gail Rosen:
Predicting Anti-microbial Resistance using Large Language Models. CoRR abs/2401.00642 (2024) - 2023
- [c27]Adriana Fasino, Emrecan Ozdogan, Bahrad A. Sokhansanj, Gail Rosen, Robi Polikar:
Semi-Supervised and Incremental Sequence Analysis for Taxonomic Classification. SSCI 2023: 1132-1138 - 2022
- [j20]Palash Pandey, Sanjeevani Arora, Gail L. Rosen:
MetaMutationalSigs: comparison of mutational signature refitting results made easy. Bioinform. 38(8): 2344-2347 (2022) - [j19]Bahrad A. Sokhansanj, Gail L. Rosen:
Predicting COVID-19 disease severity from SARS-CoV-2 spike protein sequence by mixed effects machine learning. Comput. Biol. Medicine 149: 105969 (2022) - [c26]Emrecan Ozdogan, Adriana Fasino, Rachel Nguyen, Bahrad A. Sokhansanj, Gail Rosen, Robi Polikar:
Semi-supervised and Incremental VSEARCH for Metagenomic Classification. SSCI 2022: 1119-1126 - 2021
- [j18]Zhengqiao Zhao, Stephen Woloszynek, Felix Agbavor, Joshua Chang Mell, Bahrad A. Sokhansanj, Gail L. Rosen:
Learning, visualizing and exploring 16S rRNA structure using an attention-based deep neural network. PLoS Comput. Biol. 17(9) (2021) - [c25]Mali Halac, Bahrad A. Sokhansanj, William L. Trimble, Thomas Coard, Norman C. Sabin, Emrecan Ozdogan, Robi Polikar, Gail L. Rosen:
Incremental & Semi-Supervised Learning for Functional Analysis of Protein Sequences. SSCI 2021: 1-8 - [c24]Emrecan Ozdogan, Norman C. Sabin, Thomas Gracie, Steven Portley, Mali Halac, Thomas Coard, William L. Trimble, Bahrad A. Sokhansanj, Gail Rosen, Robi Polikar:
Incremental and Semi-Supervised Learning of 16S-rRNA Genes For Taxonomic Classification. SSCI 2021: 1-7 - 2020
- [j17]Zhengqiao Zhao, Alexandru Cristian, Gail Rosen:
Keeping up with the genomes: efficient learning of our increasing knowledge of the tree of life. BMC Bioinform. 21(1): 412 (2020) - [j16]Zhengqiao Zhao, Bahrad A. Sokhansanj, Charvi Malhotra, Kitty Zheng, Gail L. Rosen:
Genetic grouping of SARS-CoV-2 coronavirus sequences using informative subtype markers for pandemic spread visualization. PLoS Comput. Biol. 16(9) (2020) - [c23]Zhengqiao Zhao, Gail Rosen:
Visualizing and Annotating Protein Sequences using A Deep Neural Network. ACSSC 2020: 506-510 - [c22]Ananya Sen Gupta, Zhengqiao Zhao, Gail Rosen:
Spatiotemporal Tracking of SARS-CoV-2 Variants using informative subtype markers and association graphs. ACSSC 2020: 516-519
2010 – 2019
- 2019
- [j15]Stephen Woloszynek, Zhengqiao Zhao, Jian Chen, Gail L. Rosen:
16S rRNA sequence embeddings: Meaningful numeric feature representations of nucleotide sequences that are convenient for downstream analyses. PLoS Comput. Biol. 15(2) (2019) - [c21]Soha Hassoun, Yasser El-Manzalawy, Georg Gerber, David Koslicki, Gail Rosen:
Workshop on Microbiomics, Metagenomics, and Metabolomics. BCB 2019: 618 - 2018
- [j14]Gregory Ditzler, Robi Polikar, Gail Rosen:
A Sequential Learning Approach for Scaling Up Filter-Based Feature Subset Selection. IEEE Trans. Neural Networks Learn. Syst. 29(6): 2530-2544 (2018) - [j13]Gregory Ditzler, Joseph LaBarck, James Ritchie, Gail Rosen, Robi Polikar:
Extensions to Online Feature Selection Using Bagging and Boosting. IEEE Trans. Neural Networks Learn. Syst. 29(9): 4504-4509 (2018) - 2017
- [c20]Zhengqiao Zhao, Jason Rollins, Linge Bai, Gail Rosen:
Incremental Author Name Disambiguation for Scientific Citation Data. DSAA 2017: 175-183 - 2015
- [j12]Gregory Ditzler, J. Calvin Morrison, Yemin Lan, Gail Rosen:
Fizzy: feature subset selection for metagenomics. BMC Bioinform. 16: 358:1-358:8 (2015) - [j11]Gregory Ditzler, Robi Polikar, Gail Rosen:
A Bootstrap Based Neyman-Pearson Test for Identifying Variable Importance. IEEE Trans. Neural Networks Learn. Syst. 26(4): 880-886 (2015) - 2014
- [j10]Loni Philip Tabb, Wei Zhao, Jingyu Huang, Gail L. Rosen:
Characterizing the Empirical Distribution of Prokaryotic Genome n-mers in the Presence of Nullomers. J. Comput. Biol. 21(10): 732-740 (2014) - [j9]Yemin Lan, J. Calvin Morrison, Ruth Hershberg, Gail L. Rosen:
POGO-DB - a database of pairwise-comparisons of genomes and conserved orthologous genes. Nucleic Acids Res. 42(Database-Issue): 625-632 (2014) - [c19]Gregory Ditzler, Gail L. Rosen:
Feature subset selection for inferring relative importance of taxonomy. BCB 2014: 673-679 - [c18]Gregory Ditzler, Matthew Austen, Gail L. Rosen, Robi Polikar:
Scaling a neyman-pearson subset selection approach via heuristics for mining massive data. CIDM 2014: 439-445 - [c17]Gregory Ditzler, Gail L. Rosen, Robi Polikar:
Domain adaptation bounds for multiple expert systems under concept drift. IJCNN 2014: 595-601 - 2013
- [j8]David Koslicki, Simon Foucart, Gail Rosen:
Quikr: a method for rapid reconstruction of bacterial communities via compressive sensing. Bioinform. 29(17): 2096-2102 (2013) - [c16]Gregory Ditzler, Gail Rosen, Robi Polikar:
Discounted expert weighting for concept drift. CIDUE 2013: 61-67 - [c15]Gregory Ditzler, Gail Rosen, Robi Polikar:
Incremental learning of new classes from unbalanced data. IJCNN 2013: 1-8 - 2012
- [j7]Gail L. Rosen, Jason Silverman, Steven D. Essinger:
Inquiry-Based Learning Through Image Processing [dsp Education]. IEEE Signal Process. Mag. 29(1): 164-169 (2012) - [j6]Xin Chen, Xiaohua Hu, Tze Yee Lim, Xiajiong Shen, E. K. Park, Gail L. Rosen:
Exploiting the Functional and Taxonomic Structure of Genomic Data by Probabilistic Topic Modeling. IEEE ACM Trans. Comput. Biol. Bioinform. 9(4): 980-991 (2012) - [c14]Gregory Ditzler, Gail Rosen, Robi Polikar:
Information theoretic feature selection for high dimensional metagenomic data. GENSiPS 2012: 143-146 - [c13]Gregory Ditzler, Gail Rosen, Robi Polikar:
Forensic identification with environmental samples. ICASSP 2012: 1861-1864 - [c12]Gregory Ditzler, Gail L. Rosen, Robi Polikar:
Transductive learning algorithms for nonstationary environments. IJCNN 2012: 1-8 - 2011
- [j5]Gail L. Rosen, Erin R. Reichenberger, Aaron M. Rosenfeld:
NBC: the Naïve Bayes Classification tool webserver for taxonomic classification of metagenomic reads. Bioinform. 27(1): 127-129 (2011) - [j4]Non G. Yok, Gail L. Rosen:
Combining gene prediction methods to improve metagenomic gene annotation. BMC Bioinform. 12: 20 (2011) - [j3]Elaine Garbarine, Joseph DePasquale, Vinay Gadia, Robi Polikar, Gail L. Rosen:
Information-theoretic approaches to SVM feature selection for metagenome read classification. Comput. Biol. Chem. 35(3): 199-209 (2011) - [c11]Steven D. Essinger, Robi Polikar, Gail Rosen:
Ordering samples along environmental gradients using particle swarm optimization. EMBC 2011: 4382-4385 - 2010
- [c10]Steven D. Essinger, Gail L. Rosen:
The Effect of Sequence Error and Partial Training Data on BLAST Accuracy. BIBE 2010: 257-262 - [c9]Non Yok, Gail Rosen:
Comparison of Gene Prediction Programs for Metagenomic Data. BIBE 2010: 291-292 - [c8]Xin Chen, Xiaohua Hu, Xiajiong Shen, Gail Rosen:
Probabilistic topic modeling for genomic data interpretation. BIBM 2010: 149-152 - [c7]Xin Chen, Xiaohua Hu, Zhongna Zhou, Caimei Lu, Gail Rosen, Tingting He, E. K. Park:
A probabilistic topic-connection model for automatic image annotation. CIKM 2010: 899-908 - [c6]Steven D. Essinger, Robi Polikar, Gail L. Rosen:
Neural network-based taxonomic clustering for metagenomics. IJCNN 2010: 1-7 - [c5]Steven D. Essinger, Gail L. Rosen:
Benchmarking BLAST Accuracy of Genus/Phyla Classification of Metagenomic Reads. Pacific Symposium on Biocomputing 2010: 10-20
2000 – 2009
- 2009
- [j2]Gail Rosen, Paul E. Hasler, Mark T. Smith:
Implementation of a Hebbian chemoreceptor model for diffusive source localization. Biosyst. 96(3): 223-236 (2009) - 2008
- [j1]Gail L. Rosen, Elaine Garbarine, Diamantino Caseiro, Robi Polikar, Bahrad A. Sokhansanj:
Metagenome Fragment Classification Using N-Mer Frequency Profiles. Adv. Bioinformatics 2008: 205969:1-205969:12 (2008) - [c4]Zhiyu Wang, MinJun Kim, Gail Rosen:
Validating models of bacterial chemotaxis by simulating the random motility coefficient. BIBE 2008: 1-5 - 2006
- [c3]Gail L. Rosen, Paul E. Hasler:
Chemical Source Localization in Unknown Turbulence Using the Cross-Correlation Method. ICASSP (3) 2006: 1116-1119 - 2003
- [c2]Gail L. Rosen, Jeffrey D. Moore:
Investigation of coding structure in DNA. ICASSP (2) 2003: 361-364 - 2002
- [c1]Gail Rosen, Jim Johnston:
Automatic loudspeaker directivity control for sound field reconstruction. ICASSP 2002: 4174
Coauthor Index
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