Luís Matos

Subject	Lossless compression algorithms for microarray images and whole genome alignments
Advisor	António J. R. Neves, Armando J. Pinho
Group
Status	PhD student
Starts	2009/10/01
Ends	2015/02/10
Country	Portugal
Projects
Past projects	DNA-Profiles, Urbis
Events
Proposals
Personal page	http://sweet.ua.pt/luismatos

Brief biography

Luís Miguel de Oliveira Matos was born in Caracas, Venezuela, in January 1985. He received his M.S. degree in computer and telematics engineering from University of Aveiro, Portugal, in July 2009. He is enrolled in the MAP-i Doctoral Programme. Currently, he is working with the Signal Processing Laboratory of Institute of Electronics and Telematics Engineering of Aveiro (IEETA) which is associated with the Department of Electronics, Telecommunications and Informatics (DETI) of University of Aveiro. His main research interests are biomedical and data compression and image/video coding. He also worked in spatiotemporal databases management systems.

Curriculum Vitae

Download English version here

Publications

Articles in international journals listed in the ISI

• Luís Matos, António J. R. Neves, Diogo Pratas, Armando J. Pinho. MAFCO: A compression tool for MAF files. PLoS ONE, vol. 10, no. 3, p. e0116082, March 2015 [IF 2015: 3.057 (Q1, 11/63)] [IF 2018: 2.776 (Q2, 24/69)]
• Luís Matos, Diogo Pratas, Armando J. Pinho. A compression model for DNA multiple sequence alignment blocks. IEEE Transactions on Information Theory, vol. 59, no. 5, p. 3189-3198, May 2013 [IF 2013: 2.650 (Q1, 14/135)]

Other articles in journals

• Luís Matos, José Moreira, Alexandre Carvalho. A spatiotemporal extension for dealing with moving objects with extent in Oracle 11g. ACM SIGAPP Applied Computing Review, vol. 12, no. 2, p. 7-17, June 2012

Chapters in books

• Luís Matos, António J. R. Neves, Armando J. Pinho. Lossy-to-Lossless Compression of Biomedical Images Based on Image Decomposition. Applications of Digital Signal Processing through Practical Approach, Sudhakar Radhakrishnan (Ed.), INTECH, p. 125-158, October 2015

Articles in conference proceedings

• Luís Matos, António J. R. Neves, Armando J. Pinho. A rate-distortion study on microarray image compression. Proceedings of the 20th Portuguese Conference on Pattern Recognition, RecPad 2014, Covilhã, Portugal, October 2014
• Luís Matos, António J. R. Neves, Armando J. Pinho. Compression of microarray images using a binary tree decomposition. Proc. of the 22nd European Signal Processing Conference, EUSIPCO-2014, Lisbon, Portugal, p. 531-535, September 2014
• Luís Matos, António J. R. Neves, Armando J. Pinho. Compression of DNA microarrays using a mixture of finite-context models. Proc. of the 18th Portuguese Conf. on Pattern Recognition, RecPad 2012, Coimbra, Portugal, October 2012
• Luís Matos, Diogo Pratas, Armando J. Pinho. Compression of whole genome alignments using a mixture of finite-context models. Proceedings of 9th International Conference on Image Analysis and Recognition, ICIAR 2012, Aveiro, Portugal, vol. Aurélio Campilho and Mohamed Kamel (Eds.): Part I, LNCS 7324, p. 359-366, June 2012
• Luís Matos, José Moreira, Alexandre Carvalho. Representation and management of Spatiotemporal data in Object-Relational Databases. SAC’ 12: Proceedings of the 2012 ACM Symposium on Applied Computing, Riva del Garda, Trento, Italy, vol. 1, p. 13-20, March 2012
• Luís Matos, António J. R. Neves, Armando J. Pinho. Lossy-to-lossless compression of microarray images using expectation pixel values. Proc. of the 17th Portuguese Conf. on Pattern Recognition, RecPad 2011, Porto, Portugal, October 2011
• Diogo Pratas, Carlos A C Bastos, Armando J. Pinho, António J. R. Neves, Luís Matos. DNA synthetic sequences generation using multiple competing Markov models. Proc. of the IEEE Workshop on Statistical Signal Processing, SSP 2011, Nice, France, p. 133-136, June 2011
• Luís Matos, António J. R. Neves, Armando J. Pinho. Lossless compression of microarray images based on background/foreground separation. Proc. of the 16th Portuguese Conf. on Pattern Recognition, RecPad 2010, Vila Real, Portugal, October 2010
• Luís Matos, António J. R. Neves, Armando J. Pinho. The New Video Coding Standard H.264/Advanced Video Coding. Proceedings of RecPad2009, Aveiro, Portugal, October 2009

PhD thesis

• Luís Matos. Lossless compression algorithms for microarray images and whole genome alignments. PhD Thesis, Universidade de Aveiro, Campus Universitário Santiago, Aveiro, Portugal, February 2015

Masters thesis

• Luís Matos. Study and Applications of the H.264 video coding standard. Masters Thesis, Universidade de Aveiro, Campus Universitário Santiago, Aveiro, Portugal, July 2009

Materials

In this section you can find images sets that were used along my research work. Some of these image set are not available in their original location anymore. Alternative public links are provided.

Microarray image sets

• ApoA1 (original download link alternative download link)
• Arizona (original download link alternative download link)
• IBB (original download link alternative download link)
• ISREC (original download link offline alternative download link)
• Omnibus - Low Mode (original download link alternative download link)
• Omnibus - High Mode (original download link alternative download link)
• Stanford (original download link offline alternative download link)
• Yeast (original download link alternative download link)
• YuLou or MicroZip (original download link offline alternative download link)

Sun image sets

• Natural (original download link alternative download link)
• Medical (original download link alternative download link)
• Other non-typical (original download link alternative download link)

mini-MIAS image set

• mini-MIAS (original download link alternative download link)

RNAi image sets

During my research, some RNAi images here also used to evaluate the performance of several compression tools. The Broad Institute of Harvard and MIT provide a set of RNAi images that can be obtained here. The set used is known as Human HT29 Colon Cancer and it can be obtained here. The files in the previous location are in DIB format but it is possible to extract the image itself using the bio-formats java library, for example.