MICA: Multiple interval-based curve alignment
MICA enables the automatic synchronization of discrete data curves. To this end, characteristic points of the curves’ shapes are identified. These landmarks are used within a heuristic curve registration approach to align profile pairs by mapping similar characteristics onto each other. In combinati...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2018-01-01
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| Series: | SoftwareX |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352711018300190 |
| _version_ | 1818968339359203328 |
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| author | Martin Mann Hans-Peter Kahle Matthias Beck Bela Johannes Bender Heinrich Spiecker Rolf Backofen |
| author_facet | Martin Mann Hans-Peter Kahle Matthias Beck Bela Johannes Bender Heinrich Spiecker Rolf Backofen |
| author_sort | Martin Mann |
| collection | DOAJ |
| description | MICA enables the automatic synchronization of discrete data curves. To this end, characteristic points of the curves’ shapes are identified. These landmarks are used within a heuristic curve registration approach to align profile pairs by mapping similar characteristics onto each other. In combination with a progressive alignment scheme, this enables the computation of multiple curve alignments.Multiple curve alignments are needed to derive meaningful representative consensus data of measured time or data series. MICA was already successfully applied to generate representative profiles of tree growth data based on intra-annual wood density profiles or cell formation data.The MICA package provides a command-line and graphical user interface. The R interface enables the direct embedding of multiple curve alignment computation into larger analyses pipelines. Source code, binaries and documentation are freely available at https://github.com/BackofenLab/MICA Keywords: Curve alignment, Landmark registration, Global alignment, Progressive alignment |
| first_indexed | 2024-12-20T14:03:07Z |
| format | Article |
| id | doaj.art-95a7ecf08ed14eda83b0780e05ed13c4 |
| institution | Directory Open Access Journal |
| issn | 2352-7110 |
| language | English |
| last_indexed | 2024-12-20T14:03:07Z |
| publishDate | 2018-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | SoftwareX |
| spelling | doaj.art-95a7ecf08ed14eda83b0780e05ed13c42022-12-21T19:38:20ZengElsevierSoftwareX2352-71102018-01-0175358MICA: Multiple interval-based curve alignmentMartin Mann0Hans-Peter Kahle1Matthias Beck2Bela Johannes Bender3Heinrich Spiecker4Rolf Backofen5Chair of Forest Growth and Dendroecology, University of Freiburg, Tennenbacher Str. 4, 79106 Freiburg, Germany; Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany; Corresponding author at: Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany.Chair of Forest Growth and Dendroecology, University of Freiburg, Tennenbacher Str. 4, 79106 Freiburg, GermanyBioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, GermanyChair of Forest Growth and Dendroecology, University of Freiburg, Tennenbacher Str. 4, 79106 Freiburg, GermanyChair of Forest Growth and Dendroecology, University of Freiburg, Tennenbacher Str. 4, 79106 Freiburg, GermanyBioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany; Center for Biological Signaling Studies (BIOSS), University of Freiburg, Schänzlestr. 18, 79104 Freiburg, Germany; Center for Biological Systems Analysis (ZBSA), University of Freiburg, Habsburgerstr. 49, 79104 Freiburg, GermanyMICA enables the automatic synchronization of discrete data curves. To this end, characteristic points of the curves’ shapes are identified. These landmarks are used within a heuristic curve registration approach to align profile pairs by mapping similar characteristics onto each other. In combination with a progressive alignment scheme, this enables the computation of multiple curve alignments.Multiple curve alignments are needed to derive meaningful representative consensus data of measured time or data series. MICA was already successfully applied to generate representative profiles of tree growth data based on intra-annual wood density profiles or cell formation data.The MICA package provides a command-line and graphical user interface. The R interface enables the direct embedding of multiple curve alignment computation into larger analyses pipelines. Source code, binaries and documentation are freely available at https://github.com/BackofenLab/MICA Keywords: Curve alignment, Landmark registration, Global alignment, Progressive alignmenthttp://www.sciencedirect.com/science/article/pii/S2352711018300190 |
| spellingShingle | Martin Mann Hans-Peter Kahle Matthias Beck Bela Johannes Bender Heinrich Spiecker Rolf Backofen MICA: Multiple interval-based curve alignment SoftwareX |
| title | MICA: Multiple interval-based curve alignment |
| title_full | MICA: Multiple interval-based curve alignment |
| title_fullStr | MICA: Multiple interval-based curve alignment |
| title_full_unstemmed | MICA: Multiple interval-based curve alignment |
| title_short | MICA: Multiple interval-based curve alignment |
| title_sort | mica multiple interval based curve alignment |
| url | http://www.sciencedirect.com/science/article/pii/S2352711018300190 |
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