Motivation
Expanding research highlights the importance of guanine quadruplex structures. Therefore, easy-accessible tools for quadruplex analyses in DNA and RNA molecules are important for the scientific community.
Results
We developed a web version of the G4Hunter application. This new web-based server is a platform-independent and user-friendly application for quadruplex analyses. It allows retrieval of gene/nucleotide sequence entries from NCBI databases and provides complete characterization of localization and quadruplex propensity of quadruplex-forming sequences. The G4Hunter web application includes an interactive graphical data representation with many useful options including visualization, sorting, data storage and export.
Availability and implementation
G4Hunter web application can be accessed at: http://bioinformatics.ibp.cz.
Supplementary information
Supplementary data are available at Bioinformatics online.
MotivationThe NCBI database contains mitochondrial DNA (mtDNA) genomes from numerous species. We investigated the presence and locations of inverted repeat sequences (IRs) in these mtDNA sequences, which are known to be important for regulating nuclear genomes.ResultsIRs were identified in mtDNA in all species. IR lengths and frequencies correlate with evolutionary age and the greatest variability was detected in subgroups of plants and fungi and the lowest variability in mammals. IR presence is non-random and evolutionary favoured. The frequency of IRs generally decreased with IR length, but not for IRs 24 or 30 bp long, which are 1.5 times more abundant. IRs are enriched in sequences from the replication origin, followed by D-loop, stem-loop and miscellaneous sequences, pointing to the importance of IRs in regulatory regions of mitochondrial DNA.Availability and implementationData were produced using Palindrome analyser, freely available on the web at http://bioinformatics.ibp.cz.Supplementary information
Supplementary data are available at Bioinformatics online.
Chloroplasts are key organelles in the management of oxygen in algae and plants and are therefore crucial for all living beings that consume oxygen. Chloroplasts typically contain a circular DNA molecule with nucleus-independent replication and heredity. Using “palindrome analyser” we performed complete analyses of short inverted repeats (S-IRs) in all chloroplast DNAs (cpDNAs) available from the NCBI genome database. Our results provide basic parameters of cpDNAs including comparative information on localization, frequency, and differences in S-IR presence. In a total of 2,565 cpDNA sequences available, the average frequency of S-IRs in cpDNA genomes is 45 S-IRs/per kbp, significantly higher than that found in mitochondrial DNA sequences. The frequency of S-IRs in cpDNAs generally decreased with S-IR length, but not for S-IRs 15, 22, 24, or 27 bp long, which are significantly more abundant than S-IRs with other lengths. These results point to the importance of specific S-IRs in cpDNA genomes. Moreover, comparison by Levenshtein distance of S-IR similarities showed that a limited number of S-IR sequences are shared in the majority of cpDNAs. S-IRs are not located randomly in cpDNAs, but are length-dependently enriched in specific locations, including the repeat region, stem, introns, and tRNA regions. The highest enrichment was found for 12 bp and longer S-IRs in the stem-loop region followed by 12 bp and longer S-IRs located before the repeat region. On the other hand, S-IRs are relatively rare in rRNA sequences and around introns. These data show nonrandom and conserved arrangements of S-IRs in chloroplast genomes.
In the contribution, there is discussed the usage of the method based on the grammatical and diff erential evolution for the automatic discovery of regression models for discrete datasets. Th e combination of these two methods enables the process to fi nd the precise structure of the mathematical model and values for the model constants separately. Th e used method is described and tested on the selected regression examples. Th e results are reported and the obtained mathematical models are presented. Th e advantages of the selected approach are described and compared to the classical methods.
In this contribution we deal with an automatic classification of economic data into multiple classes. A classifier created by grammatical evolution is used to determine the data sample membership into one of the defined classes. The grammar rules used for classifier structure creation are presented. The performance of our classifier is compared with multilayer perceptron neural network classifier and Kohonen neural network classifier. We used a survey data of consumer behaviour in food market in Czech Republic.
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