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ORCID23rd RECOMB 2019: Washington, DC, USA
- Lenore J. Cowen:
Research in Computational Molecular Biology - 23rd Annual International Conference, RECOMB 2019, Washington, DC, USA, May 5-8, 2019, Proceedings. Lecture Notes in Computer Science 11467, Springer 2019, ISBN 978-3-030-17082-0 - Fatemeh Almodaresi, Prashant Pandey, Michael Ferdman, Rob Johnson, Rob Patro:
An Efficient, Scalable and Exact Representation of High-Dimensional Color Information Enabled via de Bruijn Graph Search. 1-18 - Aryan Arbabi, David R. Adams, Sanja Fidler, Michael Brudno:
Identifying Clinical Terms in Free-Text Notes Using Ontology-Guided Machine Learning. 19-34 - Philipp Benner, Martin Vingron
:
ModHMM: A Modular Supra-Bayesian Genome Segmentation Method. 35-50 - Lodewijk Brand, Xue Yang, Kai Liu, Saad El Beleidy, Hua Wang, Hao Zhang:
Learning Robust Multi-label Sample Specific Distances for Identifying HIV-1 Drug Resistance. 51-67 - Boying Gong, Elizabeth Purdom:
MethCP: Differentially Methylated Region Detection with Change Point Models. 68-84 - Chirag Jain, Haowen Zhang, Yu Gao, Srinivas Aluru:
On the Complexity of Sequence to Graph Alignment. 85-100 - Jonathan D. Jou, Graham T. Holt, Anna U. Lowegard, Bruce Randall Donald:
Minimization-Aware Recursive K^* K ∗ ( MARK^* MARK ∗ ): A Novel, Provable Algorithm that Accelerates Ensemble-Based Protein Design and Provably Approximates the Energy Landscape. 101-119 - Mikhail Karasikov, Harun Mustafa, Amir Joudaki, Sara Javadzadeh-No, Gunnar Rätsch, André Kahles:
Sparse Binary Relation Representations for Genome Graph Annotation. 120-135 - Younhun Kim, Frederic Koehler, Ankur Moitra, Elchanan Mossel, Govind Ramnarayan:
How Many Subpopulations Is Too Many? Exponential Lower Bounds for Inferring Population Histories. 136-157 - Alan Kuhnle, Taher Mun, Christina Boucher, Travis Gagie, Ben Langmead, Giovanni Manzini:
Efficient Construction of a Complete Index for Pan-Genomics Read Alignment. 158-173 - Haoyun Lei, Bochuan Lyu, E. Michael Gertz, Alejandro A. Schäffer, Xulian Shi, Kui Wu, Guibo Li, Liqin Xu, Yong Hou, Michael Dean, Russell Schwartz:
Tumor Copy Number Deconvolution Integrating Bulk and Single-Cell Sequencing Data. 174-189 - Weihua Pan, Tao Jiang, Stefano Lonardi:
OMGS: Optical Map-Based Genome Scaffolding. 190-207 - Leonardo Pellegrina, Cinzia Pizzi, Fabio Vandin:
Fast Approximation of Frequent k-mers and Applications to Metagenomics. 208-226 - Kristoffer Sahlin, Paul Medvedev:
De Novo Clustering of Long-Read Transcriptome Data Using a Greedy, Quality-Value Based Algorithm. 227-242 - Itay Sason, Damian Wójtowicz, Welles Robinson, Mark D. M. Leiserson, Teresa M. Przytycka, Roded Sharan:
A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer. 243-255 - Ziheng Wang, Grace H. T. Yeo, Richard Sherwood, David Gifford:
Disentangled Representations of Cellular Identity. 256-271 - Ye Wu, Ruibang Luo, Henry C. M. Leung, Hing-Fung Ting, Tak Wah Lam:
RENET: A Deep Learning Approach for Extracting Gene-Disease Associations from Literature. 272-284
Short Papers
- Metin Balaban, Shahab Sarmashghi, Siavash Mirarab:
APPLES: Fast Distance-Based Phylogenetic Placement. 287-288 - Bahar Behsaz, Hosein Mohimani, Alexey A. Gurevich, Andrey D. Prjibelski, Mark F. Fisher, Larry Smarr, Pieter C. Dorrestein, Joshua S. Mylne, Pavel A. Pevzner:
De Novo Peptide Sequencing Reveals a Vast Cyclopeptidome in Human Gut and Other Environments. 289-291 - Dexiong Chen, Laurent Jacob, Julien Mairal:
Biological Sequence Modeling with Convolutional Kernel Networks. 292-293 - Van Hoan Do, Mislav Blazevic, Pablo Monteagudo, Luka Borozan, Khaled M. Elbassioni, Sören Laue, Francisca Rojas Ringeling, Domagoj Matijevic, Stefan Canzar:
Dynamic Pseudo-time Warping of Complex Single-Cell Trajectories. 294-296 - Rebecca Elyanow, Bianca Dumitrascu, Barbara E. Engelhardt, Benjamin J. Raphael:
netNMF-sc: A Network Regularization Algorithm for Dimensionality Reduction and Imputation of Single-Cell Expression Data. 297-298 - Brian Hie, Hyunghoon Cho, Benjamin Demeo, Bryan Bryson, Bonnie Berger:
Geometric Sketching of Single-Cell Data Preserves Transcriptional Structure. 299-301 - Can Kockan, Kaiyuan Zhu, Natnatee Dokmai, Nikolai Karpov, M. Oguzhan Külekci, David P. Woodruff, Süleyman Cenk Sahinalp:
Sketching Algorithms for Genomic Data Analysis and Querying in a Secure Enclave. 302-304 - Yunan Luo, Jianzhu Ma, Xiaoming Zhao, Yufeng Su, Yang Liu, Trey Ideker, Jian Peng:
Mitigating Data Scarcity in Protein Binding Prediction Using Meta-Learning. 305-307 - Joel Mefford, Danny S. Park, Zhili Zheng, Arthur Ko, Mika Ala-Korpela, Markku Laakso, Paivi Pajukanta, Jian Yang, John S. Witte, Noah Zaitlen:
Efficient Estimation and Applications of Cross-Validated Genetic Predictions. 308-310 - Matthew A. Myers, Gryte Satas, Benjamin J. Raphael:
Inferring Tumor Evolution from Longitudinal Samples. 311 - Ali Pazokitoroudi, Yue Wu, Kathryn S. Burch, Kangcheng Hou, Bogdan Pasaniuc, Sriram Sankararaman:
Scalable Multi-component Linear Mixed Models with Application to SNP Heritability Estimation. 312-313 - Shahab Sarmashghi, Vineet Bafna:
A Note on Computing Interval Overlap Statistics. 314-315 - Mike Thompson, Zeyuan Johnson Chen, Elior Rahmani, Eran Halperin:
Distinguishing Biological from Technical Sources of Variation Using a Combination of Methylation Datasets. 316-317 - Sheng Wang, Emily R. Flynn, Russ B. Altman:
GRep: Gene Set Representation via Gaussian Embedding. 318-319 - Yijie Wang, Jan Hoinka, Teresa M. Przytycka:
Accurate Sub-population Detection and Mapping Across Single Cell Experiments with PopCorn. 320-321 - Yue Wu, Anna Yaschenko, Mohammadreza Hajy Heydary, Sriram Sankararaman:
Fast Estimation of Genetic Correlation for Biobank-Scale Data. 322-323 - Jinbo Xu:
stance-Based Protein Folding Powered by Deep Learning. 324-325 - Yang Yang, Yang Zhang, Bing Ren, Jesse R. Dixon, Jian Ma:
Comparing 3D Genome Organization in Multiple Species Using Phylo-HMRF. 326-327 - Jesse M. Zhang, Govinda M. Kamath, David N. C. Tse:
Towards a Post-clustering Test for Differential Expression. 328-329 - Martin J. Zhang, Fei Xia, James Zou:
AdaFDR: A Fast, Powerful and Covariate-Adaptive Approach to Multiple Hypothesis Testing. 330-333
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