{"id":"https://openalex.org/W2220539527","doi":"https://doi.org/10.1109/bibm.2015.7359718","title":"On using Compressed Sensing and peak detection method for the Dynamic Instability parameters estimation for Microtubules modeled in three states","display_name":"On using Compressed Sensing and peak detection method for the Dynamic Instability parameters estimation for Microtubules modeled in three states","publication_year":2015,"publication_date":"2015-11-01","ids":{"openalex":"https://openalex.org/W2220539527","doi":"https://doi.org/10.1109/bibm.2015.7359718","mag":"2220539527"},"language":"en","primary_location":{"id":"doi:10.1109/bibm.2015.7359718","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2015.7359718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003386566","display_name":"Shantia Yarahmadian","orcid":"https://orcid.org/0000-0002-8088-9772"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shantia Yarahmadian","raw_affiliation_strings":["Department of Mathematics and Statistics, Mississippi State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Mississippi State University","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087934737","display_name":"Vineetha Menon","orcid":"https://orcid.org/0000-0001-6916-5346"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vineetha Menon","raw_affiliation_strings":["Department of Electrical Engineering, Mississippi State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Mississippi State University","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090582778","display_name":"Vahid Rezania","orcid":"https://orcid.org/0000-0002-5717-1244"},"institutions":[{"id":"https://openalex.org/I924318406","display_name":"MacEwan University","ror":"https://ror.org/003s89n44","country_code":"CA","type":"education","lineage":["https://openalex.org/I924318406"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Vahid Rezania","raw_affiliation_strings":["Department of Physical Sciences, Macewan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physical Sciences, Macewan University","institution_ids":["https://openalex.org/I924318406"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2261,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.86493702,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"28","issue":null,"first_page":"417","last_page":"420"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10540","display_name":"Advanced Fluorescence Microscopy Techniques","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10540","display_name":"Advanced Fluorescence Microscopy Techniques","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12162","display_name":"Cellular Automata and Applications","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10492","display_name":"Microtubule and mitosis dynamics","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/1307","display_name":"Cell Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.7556769847869873},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6432154774665833},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6202802658081055},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5701279640197754},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5576131343841553},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5435904860496521},{"id":"https://openalex.org/keywords/instability","display_name":"Instability","score":0.4927878677845001},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.48195549845695496},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.47189176082611084},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.42763012647628784},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.34918850660324097},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33050352334976196},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2636605203151703},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.24114596843719482},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.15403679013252258},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.12182152271270752}],"concepts":[{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.7556769847869873},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6432154774665833},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6202802658081055},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5701279640197754},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5576131343841553},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5435904860496521},{"id":"https://openalex.org/C207821765","wikidata":"https://www.wikidata.org/wiki/Q405372","display_name":"Instability","level":2,"score":0.4927878677845001},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.48195549845695496},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.47189176082611084},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.42763012647628784},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.34918850660324097},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33050352334976196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2636605203151703},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.24114596843719482},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.15403679013252258},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.12182152271270752},{"id":"https://openalex.org/C57879066","wikidata":"https://www.wikidata.org/wiki/Q41217","display_name":"Mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm.2015.7359718","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2015.7359718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W340244495","https://openalex.org/W1922914710","https://openalex.org/W1965404941","https://openalex.org/W1966975175","https://openalex.org/W1967110811","https://openalex.org/W1988323883","https://openalex.org/W1991863200","https://openalex.org/W1994583626","https://openalex.org/W2034286717","https://openalex.org/W2038823561","https://openalex.org/W2091603423","https://openalex.org/W2104266187","https://openalex.org/W2134435289","https://openalex.org/W2167994617","https://openalex.org/W2169382889","https://openalex.org/W2196956961","https://openalex.org/W2803670972","https://openalex.org/W3102501340","https://openalex.org/W4300263211"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2368824897","https://openalex.org/W1508050556","https://openalex.org/W1910862367","https://openalex.org/W2379365082","https://openalex.org/W2370747590","https://openalex.org/W2030109976","https://openalex.org/W2369260257","https://openalex.org/W2389120450","https://openalex.org/W55249799"],"abstract_inverted_index":{"Recent":[0],"studies":[1],"has":[2],"revealed":[3],"that":[4,102],"Microtubules":[5],"(MTs)":[6],"exhibit":[7],"three":[8,35,63],"transition":[9,36,64],"states":[10,65],"of":[11,48,66,69,72,124],"growth,":[12],"shrinkage":[13],"and":[14,51,80,112,128],"pause":[15],"states.":[16,37],"In":[17],"this":[18],"paper,":[19],"we":[20],"use":[21],"Trichotomous":[22],"Markov":[23],"Noise":[24],"(TMN)":[25],"as":[26],"a":[27],"framework":[28],"for":[29,137],"studying":[30],"MTs":[31,125],"dynamics":[32],"in":[33,55,76,84,105],"its":[34],"We":[38],"then":[39],"apply":[40,52],"Compressed":[41],"Sensing":[42],"(CS)":[43],"to":[44,59,92,116,131],"the":[45,56,62,70,78,85,90,117],"experimental":[46],"data":[47,136],"MT":[49,135],"length":[50],"peak":[53],"detection":[54],"wavelet":[57,86],"domain":[58,87],"efficiently":[60],"detect":[61],"MTs.":[67],"One":[68],"novelties":[71],"our":[73],"method":[74],"is":[75],"detecting":[77],"peaks":[79],"encoding":[81],"them":[82],"simultaneously":[83],"without":[88],"having":[89],"need":[91],"do":[93],"further":[94],"processing":[95],"after":[96],"decoding":[97],"stage.":[98],"Experimental":[99],"results":[100],"show":[101],"using":[103],"CS":[104],"conjunction":[106],"with":[107],"wavelets":[108],"provides":[109],"better":[110],"compression":[111],"reconstruction":[113],"performance":[114],"comparing":[115],"traditional":[118],"sampling":[119,139],"schemes.":[120],"Dynamic":[121],"Instability":[122],"parameters":[123],"are":[126,129],"estimated":[127],"shown":[130],"closely":[132],"approximate":[133],"original":[134],"lower":[138],"rates.":[140]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
