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Home > Research in Computational Molecular Biology: 18th Annual International Conference, RECOMB 2014, Pittsburgh, PA, USA, April 2-5, 2014, Proceedings > An Alignment-Free Regression Approach for Estimating Allele-Specific Expression Using RNA-Seq Data
Research in Computational Molecular Biology: 18th Annual International Conference, RECOMB 2014, Pittsburgh, PA, USA, April 2-5, 2014, Proceedings |
Roded Sharan
Springer International Publishing
Research in Computational Molecular Biology: 18th Annual International Conference, RECOMB 2014, Pittsburgh, PA, USA, April 2-5, 2014, Proceedings
An Alignment-Free Regression Approach for Estimating Allele-Specific Expression Using RNA-Seq Data
Authors

Chen-Ping Fu; Vladimir Jojic; Leonard McMillan

ARI Id

1674219719242_2835160

Access

Open/Free Access

Pages

69-84

DOI

10.1007/978-3-319-05269-4_6

Chapter URL

https://rd.springer.com/chapter/10.1007/978-3-319-05269-4_6

Table of Contents of Book
Showing 1 to 20 of 37 entries
Chapters/HeadingsAuthor(s)PagesInfo
Front Matter
Tractatus: An Exact and Subquadratic Algorithm for Inferring Identical-by-Descent Multi-shared Haplotype Tracts
Derek Aguiar; Eric Morrow; Sorin Istrail
1-17
HapTree: A Novel Bayesian Framework for Single Individual Polyplotyping Using NGS Data
Emily Berger; Deniz Yorukoglu; Jian Peng; Bonnie Berger
18-19
Changepoint Analysis for Efficient Variant Calling
Adam Bloniarz; Ameet Talwalkar; Jonathan Terhorst; Michael I. Jordan; David Patterson; Bin Yu et al.
20-34
On the Representation of de Bruijn Graphs
Rayan Chikhi; Antoine Limasset; Shaun Jackman; Jared T. Simpson; Paul Medvedev
35-55
Exact Learning of RNA Energy Parameters from Structure
Hamidreza Chitsaz; Mohammad Aminisharifabad
56-68
An Alignment-Free Regression Approach for Estimating Allele-Specific Expression Using RNA-Seq Data
Chen-Ping Fu; Vladimir Jojic; Leonard McMillan
69-84
The Generating Function Approach for Peptide Identification in Spectral Networks
Adrian Guthals; Christina Boucher; Nuno Bandeira
85-99
Decoding Coalescent Hidden Markov Models in Linear Time
Kelley Harris; Sara Sheehan; John A. Kamm; Yun S. Song
100-114
AptaCluster – A Method to Cluster HT-SELEX Aptamer Pools and Lessons from Its Application
Jan Hoinka; Alexey Berezhnoy; Zuben E. Sauna; Eli Gilboa; Teresa M. Przytycka
115-128
Learning Sequence Determinants of Protein: Protein Interaction Specificity with Sparse Graphical Models
Hetunandan Kamisetty; Bornika Ghosh; Christopher James Langmead; Chris Bailey-Kellogg
129-143
On Sufficient Statistics of Least-Squares Superposition of Vector Sets
Arun S. Konagurthu; Parthan Kasarapu; Lloyd Allison; James H. Collier; Arthur M. Lesk
144-159
IDBA-MTP: A Hybrid MetaTranscriptomic Assembler Based on Protein Information
Henry C. M. Leung; S. M. Yiu; Francis Y. L. Chin
160-172
MRFalign: Protein Homology Detection through Alignment of Markov Random Fields
Jianzhu Ma; Sheng Wang; Zhiyong Wang; Jinbo Xu
173-174
An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding
Shaun Mahony; Matthew D. Edwards; Esteban O. Mazzoni; Richard I. Sherwood; Akshay Kakumanu; Carolyn A. Morrison et al.
175-176
PASTA: Ultra-Large Multiple Sequence Alignment
Siavash Mirarab; Nam Nguyen; Tandy Warnow
177-191
Fast Flux Module Detection Using Matroid Theory
Arne C. Müller; Frank J. Bruggeman; Brett G. Olivier; Leen Stougie
192-206
Building a Pangenome Reference for a Population
Ngan Nguyen; Glenn Hickey; Daniel R. Zerbino; Brian Raney; Dent Earl; Joel Armstrong et al.
207-221
CSAX: Characterizing Systematic Anomalies in eXpression Data
Keith Noto; Carla Brodley; Saeed Majidi; Diana W. Bianchi; Donna K. Slonim
222-236
WhatsHap: Haplotype Assembly for Future-Generation Sequencing Reads
Murray Patterson; Tobias Marschall; Nadia Pisanti; Leo van Iersel; Leen Stougie; Gunnar W. Klau et al.
237-249
Chapters/HeadingsAuthor(s)PagesInfo
Showing 1 to 20 of 37 entries
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