Efficient algorithms for consensus string problems minimizing both distance sum and radius
The consensus (string) problem is finding a representative string, called a consensus, of a given set S of strings. In this paper we deal with consensus problems considering both distance sum and radius, where the distance sum is the sum of (Hamming) distances from the strings in S to the consensus...
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| Veröffentlicht in: | Theoretical computer science 2011-09, Vol.412 (39), p.5239-5246 |
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| creator | Amir, Amihood Landau, Gad M. Na, Joong Chae Park, Heejin Park, Kunsoo Sim, Jeong Seop |
| description | The consensus (string) problem is finding a representative string, called a consensus, of a given set
S
of strings. In this paper we deal with consensus problems considering both distance sum and radius, where the distance sum is the sum of (Hamming) distances from the strings in
S
to the consensus and the radius is the longest (Hamming) distance from the strings in
S
to the consensus. Although there have been results considering either distance sum or radius, there have been no results considering both, to the best of our knowledge.
We present the first algorithms for two consensus problems considering both distance sum and radius for three strings: one problem is to find an optimal consensus minimizing both distance sum and radius. The other problem is to find a bounded consensus such that the distance sum is at most
s
and the radius is at most
r
for given constants
s
and
r
. Our algorithms are based on characterization of the lower bounds of distance sum and radius, and thus they solve the problems efficiently. Both algorithms run in linear time. |
| doi_str_mv | 10.1016/j.tcs.2011.05.034 |
| format | Article |
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S
of strings. In this paper we deal with consensus problems considering both distance sum and radius, where the distance sum is the sum of (Hamming) distances from the strings in
S
to the consensus and the radius is the longest (Hamming) distance from the strings in
S
to the consensus. Although there have been results considering either distance sum or radius, there have been no results considering both, to the best of our knowledge.
We present the first algorithms for two consensus problems considering both distance sum and radius for three strings: one problem is to find an optimal consensus minimizing both distance sum and radius. The other problem is to find a bounded consensus such that the distance sum is at most
s
and the radius is at most
r
for given constants
s
and
r
. Our algorithms are based on characterization of the lower bounds of distance sum and radius, and thus they solve the problems efficiently. Both algorithms run in linear time.</description><identifier>ISSN: 0304-3975</identifier><identifier>EISSN: 1879-2294</identifier><identifier>DOI: 10.1016/j.tcs.2011.05.034</identifier><identifier>CODEN: TCSCDI</identifier><language>eng</language><publisher>Oxford: Elsevier B.V</publisher><subject>Algorithmics. Computability. Computer arithmetics ; Algorithms ; Applied sciences ; Artificial intelligence ; Computer science; control theory; systems ; Consensus strings ; Constants ; Distance sum ; Exact sciences and technology ; Learning and adaptive systems ; Lower bounds ; Miscellaneous ; Multiple alignments ; Optimization ; Radius ; Strings ; Theoretical computing</subject><ispartof>Theoretical computer science, 2011-09, Vol.412 (39), p.5239-5246</ispartof><rights>2011 Elsevier B.V.</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c359t-8526b00ef10eb8013eb4bfd0a1d5df09340a9552d8a951663a9da693769f2d4e3</citedby><cites>FETCH-LOGICAL-c359t-8526b00ef10eb8013eb4bfd0a1d5df09340a9552d8a951663a9da693769f2d4e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0304397511004439$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24469276$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Amir, Amihood</creatorcontrib><creatorcontrib>Landau, Gad M.</creatorcontrib><creatorcontrib>Na, Joong Chae</creatorcontrib><creatorcontrib>Park, Heejin</creatorcontrib><creatorcontrib>Park, Kunsoo</creatorcontrib><creatorcontrib>Sim, Jeong Seop</creatorcontrib><title>Efficient algorithms for consensus string problems minimizing both distance sum and radius</title><title>Theoretical computer science</title><description>The consensus (string) problem is finding a representative string, called a consensus, of a given set
S
of strings. In this paper we deal with consensus problems considering both distance sum and radius, where the distance sum is the sum of (Hamming) distances from the strings in
S
to the consensus and the radius is the longest (Hamming) distance from the strings in
S
to the consensus. Although there have been results considering either distance sum or radius, there have been no results considering both, to the best of our knowledge.
We present the first algorithms for two consensus problems considering both distance sum and radius for three strings: one problem is to find an optimal consensus minimizing both distance sum and radius. The other problem is to find a bounded consensus such that the distance sum is at most
s
and the radius is at most
r
for given constants
s
and
r
. Our algorithms are based on characterization of the lower bounds of distance sum and radius, and thus they solve the problems efficiently. Both algorithms run in linear time.</description><subject>Algorithmics. Computability. Computer arithmetics</subject><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Consensus strings</subject><subject>Constants</subject><subject>Distance sum</subject><subject>Exact sciences and technology</subject><subject>Learning and adaptive systems</subject><subject>Lower bounds</subject><subject>Miscellaneous</subject><subject>Multiple alignments</subject><subject>Optimization</subject><subject>Radius</subject><subject>Strings</subject><subject>Theoretical computing</subject><issn>0304-3975</issn><issn>1879-2294</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNp9kLtqHTEQhkVIICe2H8CdmpBq1yNppV3hyhgnNhjSxE0aodXF1mEvjkYbiJ_eOhyT0tP8MPPP7SPknEHLgKmLfVscthwYa0G2ILoPZMeGXjec6-4j2YGArhG6l5_JF8Q91JC92pHfNzEml8JSqJ0e15zK04w0rpm6dcGw4IYUS07LI33O6ziFWp3Tkub0csiNa3miPmGxiwsUt5naxdNsfdrwlHyKdsJw9qYn5OH7za_r2-b-54-766v7xgmpSzNIrkaAEBmEcQAmwtiN0YNlXvoIWnRgtZTcD1WYUsJqb5UWvdKR-y6IE_LtOLce-GcLWMyc0IVpsktYNzSaac1h4H11sqPT5RUxh2iec5pt_mcYmANGszcVozlgNCBNxVh7vr5Nt-jsFHP9NOH_Rt51SvNeVd_l0Rfqq39TyAYPWF3wKQdXjF_TO1teAVXJiQI</recordid><startdate>20110909</startdate><enddate>20110909</enddate><creator>Amir, Amihood</creator><creator>Landau, Gad M.</creator><creator>Na, Joong Chae</creator><creator>Park, Heejin</creator><creator>Park, Kunsoo</creator><creator>Sim, Jeong Seop</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>6I.</scope><scope>AAFTH</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20110909</creationdate><title>Efficient algorithms for consensus string problems minimizing both distance sum and radius</title><author>Amir, Amihood ; Landau, Gad M. ; Na, Joong Chae ; Park, Heejin ; Park, Kunsoo ; Sim, Jeong Seop</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c359t-8526b00ef10eb8013eb4bfd0a1d5df09340a9552d8a951663a9da693769f2d4e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Algorithmics. Computability. Computer arithmetics</topic><topic>Algorithms</topic><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science; control theory; systems</topic><topic>Consensus strings</topic><topic>Constants</topic><topic>Distance sum</topic><topic>Exact sciences and technology</topic><topic>Learning and adaptive systems</topic><topic>Lower bounds</topic><topic>Miscellaneous</topic><topic>Multiple alignments</topic><topic>Optimization</topic><topic>Radius</topic><topic>Strings</topic><topic>Theoretical computing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Amir, Amihood</creatorcontrib><creatorcontrib>Landau, Gad M.</creatorcontrib><creatorcontrib>Na, Joong Chae</creatorcontrib><creatorcontrib>Park, Heejin</creatorcontrib><creatorcontrib>Park, Kunsoo</creatorcontrib><creatorcontrib>Sim, Jeong Seop</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Theoretical computer science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Amir, Amihood</au><au>Landau, Gad M.</au><au>Na, Joong Chae</au><au>Park, Heejin</au><au>Park, Kunsoo</au><au>Sim, Jeong Seop</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Efficient algorithms for consensus string problems minimizing both distance sum and radius</atitle><jtitle>Theoretical computer science</jtitle><date>2011-09-09</date><risdate>2011</risdate><volume>412</volume><issue>39</issue><spage>5239</spage><epage>5246</epage><pages>5239-5246</pages><issn>0304-3975</issn><eissn>1879-2294</eissn><coden>TCSCDI</coden><abstract>The consensus (string) problem is finding a representative string, called a consensus, of a given set
S
of strings. In this paper we deal with consensus problems considering both distance sum and radius, where the distance sum is the sum of (Hamming) distances from the strings in
S
to the consensus and the radius is the longest (Hamming) distance from the strings in
S
to the consensus. Although there have been results considering either distance sum or radius, there have been no results considering both, to the best of our knowledge.
We present the first algorithms for two consensus problems considering both distance sum and radius for three strings: one problem is to find an optimal consensus minimizing both distance sum and radius. The other problem is to find a bounded consensus such that the distance sum is at most
s
and the radius is at most
r
for given constants
s
and
r
. Our algorithms are based on characterization of the lower bounds of distance sum and radius, and thus they solve the problems efficiently. Both algorithms run in linear time.</abstract><cop>Oxford</cop><pub>Elsevier B.V</pub><doi>10.1016/j.tcs.2011.05.034</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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| source | Elsevier ScienceDirect Journals; EZB-FREE-00999 freely available EZB journals |
| subjects | Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Artificial intelligence Computer science control theory systems Consensus strings Constants Distance sum Exact sciences and technology Learning and adaptive systems Lower bounds Miscellaneous Multiple alignments Optimization Radius Strings Theoretical computing |
| title | Efficient algorithms for consensus string problems minimizing both distance sum and radius |
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