Chuong B Do

Summary

Affiliation: Stanford University
Country: USA

Publications

  1. ncbi CONTRAfold: RNA secondary structure prediction without physics-based models
    Chuong B Do
    Computer Science Department, Stanford University, Stanford, CA 94305, USA
    Bioinformatics 22:e90-8. 2006
  2. ncbi A max-margin model for efficient simultaneous alignment and folding of RNA sequences
    Chuong B Do
    Computer Science Department, Stanford University, Stanford, CA 94305, USA
    Bioinformatics 24:i68-76. 2008
  3. ncbi Glocal alignment: finding rearrangements during alignment
    Michael Brudno
    Department of Computer Science, Stanford University, Stanford, CA 94305, USA
    Bioinformatics 19:i54-62. 2003
  4. ncbi CONTRAST: a discriminative, phylogeny-free approach to multiple informant de novo gene prediction
    Samuel S Gross
    Computer Science Department, Stanford University, Stanford, CA, USA
    Genome Biol 8:R269. 2007
  5. ncbi A Classifier-based approach to identify genetic similarities between diseases
    Marc A Schaub
    Department of Computer Science, Stanford University, Stanford, CA 94305, USA
    Bioinformatics 25:i21-9. 2009
  6. ncbi What is the expectation maximization algorithm?
    Chuong B Do
    Computer Science Department, Stanford University, 318 Campus Drive, Stanford, California 94305 5428, USA
    Nat Biotechnol 26:897-9. 2008
  7. ncbi Protein multiple sequence alignment
    Chuong B Do
    Computer Science Department, Stanford University, Stanford, CA, USA
    Methods Mol Biol 484:379-413. 2008
  8. ncbi Automatic parameter learning for multiple local network alignment
    Jason Flannick
    Department of Computer Science, Stanford University, Stanford, CA 94305, USA
    J Comput Biol 16:1001-22. 2009
  9. ncbi Evidence for intelligent (algorithm) design
    Balaji S Srinivasan
    Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
    Genome Biol 7:322. 2006
  10. ncbi ProbCons: Probabilistic consistency-based multiple sequence alignment
    Chuong B Do
    Department of Computer Science, Stanford University, Stanford, California 94305, USA
    Genome Res 15:330-40. 2005

Detail Information

Publications14

  1. ncbi CONTRAfold: RNA secondary structure prediction without physics-based models
    Chuong B Do
    Computer Science Department, Stanford University, Stanford, CA 94305, USA
    Bioinformatics 22:e90-8. 2006
    ....
  2. ncbi A max-margin model for efficient simultaneous alignment and folding of RNA sequences
    Chuong B Do
    Computer Science Department, Stanford University, Stanford, CA 94305, USA
    Bioinformatics 24:i68-76. 2008
    ..RAF's fast sparse dynamic programming, in turn, serves as the inference engine within a discriminative machine learning algorithm for parameter estimation...
  3. ncbi Glocal alignment: finding rearrangements during alignment
    Michael Brudno
    Department of Computer Science, Stanford University, Stanford, CA 94305, USA
    Bioinformatics 19:i54-62. 2003
    ..From the alignments we conclude that about 9% of human/mouse homology may be attributed to small rearrangements, 63% of which are duplications...
  4. ncbi CONTRAST: a discriminative, phylogeny-free approach to multiple informant de novo gene prediction
    Samuel S Gross
    Computer Science Department, Stanford University, Stanford, CA, USA
    Genome Biol 8:R269. 2007
    ..CONTRAST predicts exact coding region structures for 65% more human genes than the previous state-of-the-art method, misses 46% fewer exons and displays comparable gains in specificity...
  5. ncbi A Classifier-based approach to identify genetic similarities between diseases
    Marc A Schaub
    Department of Computer Science, Stanford University, Stanford, CA 94305, USA
    Bioinformatics 25:i21-9. 2009
    ..We show that this approach identifies the known genetic similarity between type 1 diabetes and rheumatoid arthritis, and identifies a new putative similarity between bipolar disease and hypertension...
  6. ncbi What is the expectation maximization algorithm?
    Chuong B Do
    Computer Science Department, Stanford University, 318 Campus Drive, Stanford, California 94305 5428, USA
    Nat Biotechnol 26:897-9. 2008
  7. ncbi Protein multiple sequence alignment
    Chuong B Do
    Computer Science Department, Stanford University, Stanford, CA, USA
    Methods Mol Biol 484:379-413. 2008
    ..In this chapter, we review state-of-the-art protein sequence alignment and provide practical advice for users of alignment tools...
  8. ncbi Automatic parameter learning for multiple local network alignment
    Jason Flannick
    Department of Computer Science, Stanford University, Stanford, CA 94305, USA
    J Comput Biol 16:1001-22. 2009
    ..We show that, on each of these datasets, Graemlin 2.0 has higher sensitivity and specificity than existing network aligners. Graemlin 2.0 is available under the GNU public license at http://graemlin.stanford.edu ...
  9. ncbi Evidence for intelligent (algorithm) design
    Balaji S Srinivasan
    Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
    Genome Biol 7:322. 2006
    ..A report on the 10th annual Research in Computational Molecular Biology (RECOMB) Conference, Venice, Italy, 2-5 April 2006...
  10. ncbi ProbCons: Probabilistic consistency-based multiple sequence alignment
    Chuong B Do
    Department of Computer Science, Stanford University, Stanford, California 94305, USA
    Genome Res 15:330-40. 2005
    ..On the BAliBASE, SABmark, and PREFAB benchmark alignment databases, ProbCons achieves statistically significant improvement over other leading methods while maintaining practical speed. ProbCons is publicly available as a Web resource...
  11. ncbi Effect of genetic divergence in identifying ancestral origin using HAPAA
    Andreas Sundquist
    Department of Computer Science, Stanford University, Stanford, California 94305, USA
    Genome Res 18:676-82. 2008
    ..Using HAPAA, we explore the limits of ancestry inference in closely related populations...
  12. ncbi LAGAN and Multi-LAGAN: efficient tools for large-scale multiple alignment of genomic DNA
    Michael Brudno
    Department of Computer Science, Stanford University, Stanford, California 94305-9010, USA
    Genome Res 13:721-31. 2003
    ..Multi-LAGAN is a practical method for generating multiple alignments of long genomic sequences at any evolutionary distance. Our systems are publicly available at http://lagan.stanford.edu...
  13. ncbi Multiple alignment of protein sequences with repeats and rearrangements
    Tu Minh Phuong
    Department of Computer Science, Posts and Telecommunications Institute of Technology, Hanoi, Vietnam
    Nucleic Acids Res 34:5932-42. 2006
    ..We conclude that ProDA is a practical tool for automated alignment of protein sequences with repeats and rearrangements in their domain architecture...
  14. ncbi Evolution of genes and genomes on the Drosophila phylogeny
    Andrew G Clark
    Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853, USA
    Nature 450:203-18. 2007
    ..These may prove to underlie differences in the ecology and behaviour of these diverse species...