EGNAT: A Fully Dynamic Metric Access Method for Secondary Memory

Background: DNA and Protein sequences of an organism contain a variety of repeated structures of various types. These repeated structures play an important role in Molecular biology as they are related to genetic backgrounds of inherited diseases. They also serve as a marker for DNA mapping and DNA fingerprinting. Efficient searching of maximal and super maximal repeats in DNA/Protein sequences can lead to many other applications in the area of genomics. Moreover, these repeats can also be used for identification of critical diseases by finding the similarity between frequency distributions of repeats in viruses and genomes (without using alignment algorithms). Objective: The study aims to develop an efficient tool for searching maximal and super maximal repeats in large DNA/Protein sequences. Methods: The proposed tool uses a newly introduced data structure Induced Enhanced Suffix Array (IESA). IESA is an extension of enhanced suffix array. It uses induced suffix array instead of classical suffix array. IESA consists of Induced Suffix Array (ISA) and an additional array-Longest Common Prefix (LCP) array. ISA is an array of all sorted suffixes of the input sequence while LCP array stores the lengths of the longest common prefixes between all pairs of consecutive suffixes in an induced suffix array. IESA is known to be efficient w.r.t. both time and space. It facilitates the use of secondary memory for constructing the large suffix-array. Results: An open source standalone tool named MSR-IESA for searching maximal and super maximal repeats in DNA/Protein sequences is provided at https://github.com/sanjeevalg/MSRIESA. Experimental results show that the proposed algorithm outperforms other state of the art works w.r.t. to both time and space. Conclusion: The proposed tool MSR-IESA is remarkably efficient for the analysis of DNA/Protein sequences, having maximal and super maximal repeats of any length. It can be used for identification of well-known diseases.

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Ready Access to Molecular Rotors Based on Boron Dipyrromethene Dyes-Coumarin Dyads Featuring Broadband Absorption

Molecules ◽

10.3390/molecules25040781 ◽

2020 ◽

Vol 25 (4) ◽

pp. 781

Author(s):

Ernesto Enríquez-Palacios ◽

Teresa Arbeloa ◽

Jorge Bañuelos ◽

Claudia I. Bautista-Hernández ◽

José G. Becerra-González ◽

...

Keyword(s):

Molecular Rotors ◽

Fluorescence Signal ◽

Access Method ◽

Broadband Absorption ◽

Boron Dipyrromethene ◽

Conformational Freedom ◽

Meso Position ◽

Photophysical Study ◽

Ready Access

Herein we report on a straightforward access method for boron dipyrromethene dyes (BODIPYs)-coumarin hybrids linked through their respective 8- and 6- positions, with wide functionalization of the coumarin fragment, using salicylaldehyde as a versatile building block. The computationally-assisted photophysical study unveils broadband absorption upon proper functionalization of the coumarin, as well as the key role of the conformational freedom of the coumarin appended at the meso position of the BODIPY. Such free motion almost suppresses the fluorescence signal, but enables us to apply these dyads as molecular rotors to monitor the surrounding microviscosity.

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Selection of Access Method for a Set of Table Records in a Relational Databases

2020 ELEKTRO ◽

10.1109/elektro49696.2020.9130261 ◽

2020 ◽

Author(s):

Aleksey I. Baranchikov ◽

Pavel A. Baranchikov ◽

Sergey I. Babaev ◽

Andrey S. Tarasov

Keyword(s):

Relational Databases ◽

Access Method ◽

Selection Of

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Cache-efficient sweeping-based interval joins for extended Allen relation predicates

The VLDB Journal ◽

10.1007/s00778-020-00650-5 ◽

2021 ◽

Author(s):

Danila Piatov ◽

Sven Helmer ◽

Anton Dignös ◽

Fabio Persia

Keyword(s):

Data Structure ◽

Experimental Evaluation ◽

State Of The Art ◽

Temporal Databases ◽

Access Method ◽

Wide Range ◽

Interval Relation ◽

Cache Efficient ◽

Join Algorithms ◽

Better Than

AbstractWe develop a family of efficient plane-sweeping interval join algorithms for evaluating a wide range of interval predicates such as Allen’s relationships and parameterized relationships. Our technique is based on a framework, components of which can be flexibly combined in different manners to support the required interval relation. In temporal databases, our algorithms can exploit a well-known and flexible access method, the Timeline Index, thus expanding the set of operations it supports even further. Additionally, employing a compact data structure, the gapless hash map, we utilize the CPU cache efficiently. In an experimental evaluation, we show that our approach is several times faster and scales better than state-of-the-art techniques, while being much better suited for real-time event processing.

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