Special Issue "Data Compression"

Assistant Editor
Ms. Laura Simon
MDPI, Kandererstrasse 25, CH-4057 Basel, Switzerland
E-Mail:

Guest Editor
Dr. David Salomon
Computer Science Department (Retired), California State University, Northridge, CA 91330-8281, USA
Website: http://www.davidsalomon.name/
E-Mail:
Interests: computer graphics; data compression; cryptography

Data compression is the operation of converting an input data file to a smaller file. This operation is important for the following reasons: 1. People like to accumulate data. Thus, no matter how big a storage device one has, sooner or later it is going to fill up. 2. People hate to wait for data transfers. We often upload and download files from our computers and we hate to wait for long, slow data transfers. How can data be compressed? We can represent the same amount of information in fewer bits because the original data representation is not the shortest possible. It is intentionally long in order to simplify processing the data. We say that our data representations have redundancies. Compressing data is done by locating its redundancies and reducing or eliminating them. Thus, the field of data compression tries to understand the sources of redundancies in different types of data and find clever methods to eliminate them. Today, after decades of research, there are hundreds of algorithms and dozens of implementations that can reduce the size of all types of digital data. It is my hope that this issue of Algorithms will make a significant contribution toward this goal.

Submission

All papers should be submitted to algorithms@mdpi.org. To be published continuously until the deadline and papers will be listed together at the special issue website.

Submitted papers should not have been published nor be under consideration for publication elsewhere. All papers are refereed through a peer-review process. A guide for authors is available on the Instructions for Authors page. Algorithms is an international peer-reviewed quarterly journal published by Molecular Diversity Preservation International.

Article Processing Charges (APC) will be waived for well prepared manuscripts of invited papers. For the first three volumes of this new journal the APC are of 300 CHF (or 550 CHF per paper for those papers that require extensive additional formatting and/or English corrections) for papers submitted before 31 December 2010.

• data compression
• data coding
• source coding
• information theory
• entropy
• data redundancy
• variable-length codes

Title: Data Compression Algorithms and their Applications to Bioinformatics
Authors: Ö. U. Nalbantoglu, K. Sayood and D. Russell
Affiliation: Department of Electrical Engineering, University of Nebraska, Lincoln, NE 68588-0511, USA; E-Mail: ksayood@eecomm.unl.edu
Abstract: Data compression at its base is concerned with how information is organized in data. Understanding this organization can lead to efficient ways of representing the information and hence data compression. In this paper we review the ways in which ideas and approaches fundamental to the theory and practice of data compression have been used in the area of bioinformatics. We look at how some of the ideas behind the popular Lempel-Ziv compression algorithms have been used to infer phylogenetic relationships between organisms, develop multiple sequence alignments for very large data-sets, and infer relationships between partial genomic sequences. We will also examine how basic theoretical ideas from data compression, such as the notions of entropy and mutual information, have been used for analyzing biological sequences in order to discover hidden patterns and to develop techniques for segmenting large genomes in a biologically informative manner. Finally, we look at how the theoretical concepts which underlie many data compression algorithms can be used to advance our understanding of microbial communities that inhabit our bodies and our environment.

Type of Paper: Article
Title: Compressed Matching in Dictionaries
Authors: Shmuel T. Klein and Dana Shapira; E-Mail: tomi@cs.biu.ac.il

Type of Paper: Article
Title: Recognition of Pulmonary Nodules in Thoracic CT Scans Using
3-D Deformable Object Models of Different Classes
Authors: Hotaka Takizawa, Shinji Yamamoto and Tsuyoshi Shiina; E-Mail: takizawa@cs.tsukuba.ac.jp

Type of Paper: Article
Title: Suffix-Sorting via Shannon-Fano-Elias Codes
Authors: Don Adjeroh and Fei Nan; E-Mail: don@csee.wvu.edu