The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
An expectation maximization (EM) algorithm for the identification and characterization of common sites in unaligned biopolymer sequences
Abstract
Statistical methodology for the identification and characterization of protein binding sites in a set of unaligned DNA fragments is presented. Each sequence must contain at least one common site. No alignment of the sites is required. Instead, the uncertainty in the location of the sites is handled by employing the missing information principle to develop an “expectation maximization” (EM) algorithm. This approach allows for the simultaneous identification of the sites and characterization of the binding motifs. The reliability of the algorithm increases with the number of fragments, but the computations increase only linearly. The method is illustrated with an example, using known cyclic adenosine monophophate receptor protein (CRP) binding sites. The final motif is utilized in a search for undiscovered CRP binding sites.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
Statistical Analysis With Missing Data
Lahiff, M., Little, R. J. A., & Rubin, D. B. (1989) · Journal of the American Statistical Association · doi:10.2307/2289883 · Cited by 17,265
Improved tools for biological sequence comparison.
Pearson, W. R., & Lipman, D. J. (1988) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.85.8.2444 · Cited by 11,227
The Advanced Theory of Statistics.
Clarke, G. M., Kendall, M., & Stuart, A. (1978) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2344782 · Cited by 6,658
Statistical Analysis With Missing Data
Ghosh, S. (1988) · Technometrics · doi:10.1080/00401706.1988.10488446 · Cited by 4,576
Mixture Densities, Maximum Likelihood and the EM Algorithm
Redner, R. A., & Walker, H. F. (1984) · SIAM Review · doi:10.1137/1026034 · Cited by 2,693
Exploratory latent structure analysis using both identifiable and unidentifiable models
GOODMAN, L. A. (1974) · Biometrika · doi:10.1093/biomet/61.2.215 · Cited by 1,637
Sequence-specific recognition of double helical nucleic acids by proteins.
Seeman, N. C., Rosenberg, J. M., & Rich, A. (1976) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.73.3.804 · Cited by 1,125
Promoter-specific activation of RNA polymerase II transcription by Sp1
Kadonaga, J. T., Jones, K. A., & Tjian, R. (1986) · Trends in Biochemical Sciences · doi:10.1016/0968-0004(86)90226-4 · Cited by 1,012
Selection of DNA binding sites by regulatory proteins
Berg, O. G., & von Hippel, P. H. (1987) · Journal of Molecular Biology · doi:10.1016/0022-2836(87)90354-8 · Cited by 744
Cyclic AMP Receptor Protein: Role in Transcription Activation
de Crombrugghe, B., Busby, S., & Buc, H. (1984) · Science · doi:10.1126/science.6372090 · Cited by 621
Escherichia coli promoter sequences predict in vitro RNA polymerase selectivity
Mulligan, M. E., Hawley, D. K., Entriken, R., & McClure, W. R. (1984) · Nucleic Acids Research · doi:10.1093/nar/12.1part2.789 · Cited by 473
Identifying protein-binding sites from unaligned DNA fragments.
Stormo, G. D., & Hartzell, G. W. (1989) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.86.4.1183 · Cited by 460
The DNA binding domain and bending angle of E. coli CAP protein
Liu-Johnson, H.-N., Gartenberg, M. R., & Crothers, D. M. (1986) · Cell · doi:10.1016/0092-8674(86)90814-7 · Cited by 318
Estimation and Hypothesis Testing in Finite Mixture Models
Aitkin, M., & Rubin, D. B. (1985) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1985.tb01331.x · Cited by 308
Promoters of Escherichia coli: a hierarchy of in vivo strength indicates alternate structures.
Deuschle, U., Kammerer, W., Gentz, R., & Bujard, H. (1986) · The EMBO Journal · doi:10.1002/j.1460-2075.1986.tb04596.x · Cited by 308
Brosius, J., Cate, R. L., & Perlmutter, A. P. (1982) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(18)34261-3 · Cited by 211
Weber, I. T., & Steitz, T. A. (1984) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.81.13.3973 · Cited by 131
Raibaud, O., Vidal-Ingigliardi, D., & Richet, E. (1989) · Journal of Molecular Biology · doi:10.1016/0022-2836(89)90218-0 · Cited by 88
Efficient algorithms for molecular sequence analysis.
Karlin, S., Morris, M. S., Ghandour, G., & Leung, M. (1988) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.85.3.841 · Cited by 48
Cited by
Hertz, G. Z., & Stormo, G. D. (1999) · Bioinformatics · doi:10.1093/bioinformatics/15.7.563 · Cited by 1,243
Tusnády, G. E., & Simon, I. (1998) · Journal of Molecular Biology · doi:10.1006/jmbi.1998.2107 · Cited by 1,079
What is the expectation maximization algorithm?
Do, C. B., & Batzoglou, S. (2008) · Nature Biotechnology · doi:10.1038/nbt1406 · Cited by 607
Probabilistic discovery of time series motifs
Chiu, B., Keogh, E., & Lonardi, S. (2003) · Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/956750.956808 · Cited by 573
Hidden Markov models of biological primary sequence information.
Baldi, P., Chauvin, Y., Hunkapiller, T., & McClure, M. A. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.3.1059 · Cited by 450
Metadata
- Authors
- Lawrence, C. E., & Reilly, A. A.
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 1990-01
- Volume
- 7
- Issue
- 1
- Pages
- 41-51
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W2048869777
- Cited by
- 526
- References
- 20
- FWCI
- 1.35
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.