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Sequencing-by-hybridization revisited: the analog-spectrum proposal
Abstract
All published approaches to DNA sequencing by hybridization (SBH) consist of the biochemical acquisition of the spectrum of a target sequence (the set of its subsequences conforming to a given probing pattern) followed by the algorithmic reconstruction of the sequence from its spectrum. In the "standard" or "uniform" approach, the probing pattern is a string of length L and the length of reliably reconstructible sequences is known to be mlen = O(2(L)). For a fixed microarray area, higher sequencing performance can be achieved by inserting nonprobing gaps ("wild-cards") in the probing pattern. The reconstruction, however, must cope with the emergence of fooling probes due to the gaps and algorithmic failure occurs when the spectrum becomes too densely populated, although we can achieve mcomp = 0(4(L)). Despite the combinatorial success of gapped probing, all current approaches are based on a biochemically unrealistic spectrum-acquisition model (digital-spectrum). The reality of hybridization is much more complex. Departing from the conventional model, in this paper, we propose an alternative, called the analog-spectrum model, which more closely reflects the biochemical process. This novel modeling reestablishes probe length as the performance-governing factor, adopting "semidegenerate bases" as suitable emulators of currently inadequate universal bases. One important conclusion is that accurate biochemical measurements are pivotal to the success of SBH. The theoretical proposal presented in this paper should be a convincing stimulus for the needed biotechnological work.
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Cites
Thermodynamics and NMR of Internal G·T Mismatches in DNA
Allawi, H. T., & SantaLucia, J. (1997) · Biochemistry · doi:10.1021/bi962590c · Cited by 623 · cited 1×
“Energy parameters have also been determined for mismatches [1], [2], [3], [4].”
Background
Cited by
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Ng, R. T., & Han, J. (2002) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2002.1033770 · Cited by 1,202
Maurer, C. R., Qi, R., & Raghavan, V. (2003) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2003.1177156 · Cited by 911
Efficient collision detection using bounding volume hierarchies of k-DOPs
Klosowski, J. T., Held, M., Mitchell, J. S. B., Sowizral, H., & Zikan, K. (1998) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/2945.675649 · Cited by 873
Outlier mining in large high-dimensional data sets
Angiulli, F., & Pizzuti, C. (2005) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2005.31 · Cited by 365
Metadata
- Authors
- Preparata, F. P.
- Venue
- IEEE/ACM Transactions on Computational Biology and Bioinformatics
- Published
- 2004-01
- Volume
- 1
- Issue
- 1
- Pages
- 46-52
- ISSN
- 1545-5963 (ISSN-L)
- OpenAlex
- W2167862746
- Cited by
- 320
- References
- 1
- FWCI
- 23.38
- Type
- journal article
- Language
- en
- Open access
- closed
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