### Abstract

Given a set of m molecules, derived from K homologous clones, we wish to partition these molecules into K populations, each giving rise to distinct ordered restriction maps, thus providing simple means for studying biological variations. With the emergence of single-molecule methods, such as optical mapping, that can create individual ordered restriction maps reliably and with high throughput, it becomes interesting to study the related algorithmic problems. In particular, we provide a complete computational complexity analysis of the "K-populations" problem along with a probabilistic analysis. We also present some simple polynomial heuristics, while exposing the relations among various error sources that the optical mapping approach may need to cope with. We believe that these results will be of interest to computational biologists in devising better algorithms, to biochemists in understanding the trade-offs among the error sources and finally, to biologists in creating reliable protocols for population study.

Original language | English (US) |
---|---|

Pages (from-to) | 203-227 |

Number of pages | 25 |

Journal | Discrete Applied Mathematics |

Volume | 104 |

Issue number | 1-3 |

State | Published - Aug 15 2000 |

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### ASJC Scopus subject areas

- Computational Theory and Mathematics
- Applied Mathematics
- Discrete Mathematics and Combinatorics
- Theoretical Computer Science

### Cite this

*Discrete Applied Mathematics*,

*104*(1-3), 203-227.

**Partitioning single-molecule maps into multiple populations : Algorithms and probabilistic analysis.** / Parida, Laxmi; Mishra, Bud.

Research output: Contribution to journal › Article

*Discrete Applied Mathematics*, vol. 104, no. 1-3, pp. 203-227.

}

TY - JOUR

T1 - Partitioning single-molecule maps into multiple populations

T2 - Algorithms and probabilistic analysis

AU - Parida, Laxmi

AU - Mishra, Bud

PY - 2000/8/15

Y1 - 2000/8/15

N2 - Given a set of m molecules, derived from K homologous clones, we wish to partition these molecules into K populations, each giving rise to distinct ordered restriction maps, thus providing simple means for studying biological variations. With the emergence of single-molecule methods, such as optical mapping, that can create individual ordered restriction maps reliably and with high throughput, it becomes interesting to study the related algorithmic problems. In particular, we provide a complete computational complexity analysis of the "K-populations" problem along with a probabilistic analysis. We also present some simple polynomial heuristics, while exposing the relations among various error sources that the optical mapping approach may need to cope with. We believe that these results will be of interest to computational biologists in devising better algorithms, to biochemists in understanding the trade-offs among the error sources and finally, to biologists in creating reliable protocols for population study.

AB - Given a set of m molecules, derived from K homologous clones, we wish to partition these molecules into K populations, each giving rise to distinct ordered restriction maps, thus providing simple means for studying biological variations. With the emergence of single-molecule methods, such as optical mapping, that can create individual ordered restriction maps reliably and with high throughput, it becomes interesting to study the related algorithmic problems. In particular, we provide a complete computational complexity analysis of the "K-populations" problem along with a probabilistic analysis. We also present some simple polynomial heuristics, while exposing the relations among various error sources that the optical mapping approach may need to cope with. We believe that these results will be of interest to computational biologists in devising better algorithms, to biochemists in understanding the trade-offs among the error sources and finally, to biologists in creating reliable protocols for population study.

UR - http://www.scopus.com/inward/record.url?scp=0346108622&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0346108622&partnerID=8YFLogxK

M3 - Article

VL - 104

SP - 203

EP - 227

JO - Discrete Applied Mathematics

JF - Discrete Applied Mathematics

SN - 0166-218X

IS - 1-3

ER -