DNA and RNA sequences

Part 1 of this two-part article series reviews the history of slalom chromatography (SC), the rationale for its recent revival, and the updated mechanistic framework of this technique. Rooted in the fundamental physical properties of deoxyribonucleic acid/ribonucleic acid (DNA/RNA) biopolymers and laminar flow dynamics in packed chromatographic beds, SC is highlighted for its most promising applications in cell and gene therapy. Recent two-year experimental investigations have revealed that SC operates through an out‑of‑equilibrium mechanism, coupling the entropic elasticity of double‑stranded deoxyribonucleic acid/ribonucleic acid (dsDNA/RNA) with the extension and shear forces generated within the interparticle spaces of ultrahigh-pressure liquid chromatography (UHPLC) columns. In contrast to gel permeation chromatography (GPC) or hydrodynamic chromatography (HDC), SC functions at high speed and uniquely elutes smaller dsDNA fragments first, followed by progressively larger ones. Unlike agarose gel electrophoresis (AGE), SC achieves separations of large DNAs in less than three minutes, with nearly twice the resolution power of typical AGE. These findings paved the way for the recent design of a new SC column intended for use in cell and gene therapy as an alternative to standard AGE. Further applications of this new SC column within cell and gene therapy workflows will be discussed in Part 2.

Cancer, a pervasive global health issue, accounts for approximately 9 million deaths annually. The survival rate of cancer patients significantly improves with early detection and accurate staging. In this context, ribonucleic acid sequencing (RNA-Seq) has become a powerful technique for measuring gene expression, thereby playing a crucial role in human disease research. On the other hand, there is a need for more efficient computational resources and tools for analysing RNA-Seq data. The RNA-Seq datasets known as the Cancer Genome Atlas (TCGA) were used in this research. In contrast, The following five types of cancer are included: Colon Adenocarcinoma, Prostate Adenocarcinoma, Renal Clear Cell Carcinoma, Lung Adenocarcinoma, and Breast Invasive Carcinoma. This research proposes a machine-learning technique based on the AdaBoost classifier for detecting, classifying, and predicting breast cancer. The findings of our proposed method exhibit remarkable performance, achieving a cross-validation accuracy of 99.77%, while the test and prediction accuracy were 100%. Critical parameters such as precision, recall, support, F1-score, and accuracy support this performance.

CpG islands are genomic regions characterized by high GC content and a high frequency of CpG dinucleotides. These regions play crucial roles in gene regulation and often associated with gene promoters. Identifying CpG islands computationally involves analyzing DNA sequences to locate stretches that meet specic criteria for GC content and CpG ratio. we present a method to identify CpG islands using a computational approach based on a sliding window technique. The criteria for identifying CpG islands include a GC content threshold with a minimum of 50% GC content in a sliding window of 200 base pairs and a CpG ratio threshold with an observed-to-expected ratio of CpG dinucleotides of at least 0.6 within the same window. Accurate identication of these regions is crucial for understanding gene regulation, epigenetic modications, and their roles in various biological processes and diseases. This study also explores the use of Hidden Markov Models (HMMs) for detecting CpG islands in DNA sequences. HMMs provide a robust probabilistic framework to model the sequence characteristics of CpG islands. The states of the HMM represent regions with high GC content and dense CpG dinucleotides (CpG island state) and regions with lower GC content (background state). Transition and emission probabilities are estimated using training data, and the Viterbi algorithm is employed to nd the most likely sequence of hidden states, enabling the identication of CpG islands.

The integration of traditional Chinese metaphysical concepts, such as I Ching (易經)， Ba Gua (八卦)，Bi Gua (Hexagrams), Five Elements (五行), Ten Heavenly Stems (十天干)， and Twelve Earthly Branches (十二地支)， with modem scientific theories, particularly genetic structures (DNA and RNA), represents a groundbreaking theoretical framework. This manuscript presents a novel approach to unifying these elements under the Double Helix-Triplex Model, which incorporates the structural and informational principles of DNA and mRNA synthesis with the metaphysical systems of
fortune-telling, Feng Shui (風水)，Ba Zi (八字)，and Qi (氣).

In this work, DNA (de-oxy ribonucleic acid) sequences are transformed to binary sequences to explore the dissimilarities between different species. A mathematical approach has been reported and implemented to establish phylogenetic networks by using the concept of hamming distances on binary sequences to explore the evolutionary history of the species. A program is also coded in python language for the conversion of DNA sequences as well as to find the hamming distances among them.

A maximum entropy principle (MEP) governing the distribution of complexity of short oligonucleotides from large collections of functionally equivalent sequences is presented. The principle is seen to work well in both translated regions (exons and bacterial genes) and introns from various genomes. It also works in cases of sample sequences from various genomes and even a representative sample of the entire GenBank. This suggests that all naturally occurring DNA sequences are likely to follow the MEP described in this report. The linear trend of surprisal as a function of complexity is systematically characterized by remarkably different slope values for introns and translated regions of genes from all eukaryotic genomes studied (primates, rodents, other mammals, other vertebrates, invertebrates, organella, plants and viruses). This fact may be used as a criterion for discriminant analysis.

Previous reports showed that consecutive incorporations of triazole-modified 2′-deoxyuridines stabilized DNA•DNA and DNA•RNA duplexes due to additional πstacking between triazole moieties. In this work, several triazole-modified thymidines (1-3) have been synthesized via Cu-catalyzed azide-alkyne cycloaddition reaction and incorporated into oligodeoxyribonucleotides (ODNs). Compounds 1-3 decreased the stability of DNA•DNA and DNA• RNA duplexes. Among these triazole-modified thymidines, 3 with a coumarin-modified triazole moiety showed the most destabilizing effect on ODN duplexes while 1 with an unsubstituted triazole moiety showed the least destabilizing effect. These data suggested that a bulky substituent at the 4 position of triazole ring further destabilizes DNA duplex possibly due to steric hindrance interfering Watson-Crick base pairing. The destabilizing effect per modified nucleoside is smaller for two or three consecutive incorporations than single incorporation. Density functional theory computation suggested the presence of π-stacking interactions among the modified triazole moieties at the C5-methyl group of thymine, which may slightly stabilize the DNA duplex. However, due to the noncoplanar conformation between the modified triazole groups and thymine moieties, the destabilizing effect caused by the steric hindrance is larger than the stabilizing effect arisen from π-stacking. Although the triazole moieties slightly alter the pK a values of thymidine, they did not affect the pH dependence of DNA duplex stability. Similar to native ODNs, the stability of the DNA duplexes containing 1-3 decreased in the following order: pH 7.0/ pH 8.0 > pH 6.0 > pH 9.0 > pH 5.0. Our study provides additional insights into and a novel guide for duplexes' thermal stability caused by base modifications.

Previous reports showed that consecutive incorporations of triazole-modified 2′-deoxyuridines stabilized DNA·DNA and DNA·RNA duplexes due to additional π-stacking between triazole moieties. In this work, severaltriazole-modified thymidines (1−3) have been synthesized viaCu-catalyzed azide−alkyne cycloaddition reaction and incorporated into oligodeoxyribonucleotides (ODNs). Compounds 1−3 decreased the stability of DNA·DNA and DNA·RNA duplexes. Among these triazole-modified thymidines, 3with a coumarin-modified triazole moiety showed the most destabilizing effect on ODN duplexes while 1 with an unsubstituted triazole moiety showed the least destabilizing effect. These data suggested that a bulky substituent at the 4 positions of triazole ring further destabilizes DNA duplex possibly due to steric hindrance interfering Watson−Crick base pairing. The destabilizing effect per modified nucleoside is smaller fortwo or three consecutive incorporations than single incorporation. Density functional theory computation suggested the presence of π-stacking interactions among the modified triazole moieties at the C5-methyl group of thymine, which may slightly stabilize the DNA duplex. However, due to the noncoplanar conformation between the modified triazole groups and thyminemoieties, the destabilizing effect caused by the steric hindrance is larger than the stabilizing effect arisen from π-stacking. Although the triazole moieties slightly alter the pKa values of thymidine, they did not affect the pH dependence of DNA duplex stability. Similar to native ODNs, the stability of the DNA duplexes containing 1−3 decreased in the following order: pH 7.0/pH 8.0 > pH 6.0 > pH 9.0 > pH 5.0. Our study provides additional insights into and a novel guide for duplexes’ thermal stability caused by base modifications

The development of efficient data compressors for DNA sequences is crucial not only for reducing the storage and the bandwidth for transmission, but also for analysis purposes. In particular, the development of improved compression models directly influences the outcome of anthropological and biomedical compression-based methods. In this paper, we describe a new lossless compressor with improved compression capabilities for DNA sequences representing different domains and kingdoms. The reference-free method uses a competitive prediction model to estimate, for each symbol, the best class of models to be used before applying arithmetic encoding. There are two classes of models: weighted context models (including substitutional tolerant context models) and weighted stochastic repeat models. Both classes of models use specific sub-programs to handle inverted repeats efficiently. The results show that the proposed method attains a higher compression ratio than state-of-the-art approaches...

The Analytic visualization suggests representing knowledge during a visual type that may be charts, graphs, lists, or maps. The COVID 19 detection and analysis of spreading is very important for countries. Database management with respect to virus deep analysis is a critical task to the researcher through conventional algorithms. The RNA, DNA, and biological data are helping to the bio-inspired algorithm but its implementation can be complex by software tools. Therefore, an effective technique is required to cross over the above limitations. So that covid 19 pandemic data analysis is performed through FCNN (Fully conventional Neural Network) pre-training network. The dataset is collected from social media, Kaggle, and GitHub databases. At 1st stage, the auto stack encoding process is applied later same data is processed with FCNN deep learning classifier. In this research work, covid-pandemic affects parameters like infected persons, deaths, active cases, and recovering cases. The FCNN is take care of feature extraction, training, testing, and classification. Finally using a confusion matrix accuracy of 98.34%, sensitivity 97.63%, Recall 98.26%, and F measure 98.83% had been estimated.

The development of efficient data compressors for DNA sequences is crucial not only for reducing the storage and the bandwidth for transmission, but also for analysis purposes. In particular, the development of improved compression models directly influences the outcome of anthropological and biomedical compression-based methods. In this paper, we describe a new lossless compressor with improved compression capabilities for DNA sequences representing different domains and kingdoms. The reference-free method uses a competitive prediction model to estimate, for each symbol, the best class of models to be used before applying arithmetic encoding. There are two classes of models: weighted context models (including substitutional tolerant context models) and weighted stochastic repeat models. Both classes of models use specific sub-programs to handle inverted repeats efficiently. The results show that the proposed method attains a higher compression ratio than state-of-the-art approaches...

In algorithmic information theory, the Kolmogorov complexity of an object is the length of the shortest computer program that produces the object as output. It is a measure of the computational resources needed to specify the object. However, Kolmogorov complexity is non-computable as such, it can only be approximately attainable. One of the most notable approximations are data compressors, since the bitstream produced by a lossless data compression algorithm allows the reconstruction of the original data with the appropriate decoder, and therefore can be seen as an upper bound of the algorithmic complexity of the sequence. In this paper, we evaluate the usage of the Normalized Compression (NC) as the compression measure for analysing various Virus DNA sequences and evaluate how it changes when substitutions and permutations are performed on the DNA sequences. Finally, we draw conclusions regarding the nature of these sequences.

The development of efficient data compressors for DNA sequences is crucial not only for reducing the storage and the bandwidth for transmission, but also for analysis purposes. In particular, the development of improved compression models directly influences the outcome of anthropological and biomedical compression-based methods. In this paper, we describe a new lossless compressor with improved compression capabilities for DNA sequences representing different domains and kingdoms. The reference-free method uses a competitive prediction model to estimate, for each symbol, the best class of models to be used before applying arithmetic encoding. There are two classes of models: weighted context models (including substitutional tolerant context models) and weighted stochastic repeat models. Both classes of models use specific sub-programs to handle inverted repeats efficiently. The results show that the proposed method attains a higher compression ratio than state-of-the-art approaches, on a balanced and diverse benchmark, using a competitive level of computational resources. An efficient implementation of the method is publicly available, under the GPLv3 license.

Acinetobacterbaumannii (A. baumannii) is one of the newly launched foodborne bacterium,which acts as an opportunistic pathogen originated from different infection sources, including contaminated water and environment and through human manipulation of seafood samples [3]. It is an aerobic, Gramnegative,rod and non-fermenting bacteriumthat colonizes the respiratory tract, skin, urinary and gastrointestinal systems[4]. The bacterium is also responsible for surgical infections, pneumonia, catheter-related blood circulatory, and urinary tract infection, mediastinitis, meningitis, cholangitis,and osteomyelitis [5].

Network Biology
ISSN 2220-8879
CODEN NBEICS
E-mail: [email protected]

Volume 12, Number 1, 1 March 2022 
http://www.iaees.org/publications/journals/nb/articles/2022-12(1)/2022-12(1).asp

Cover Pages
[Front Pages (156K)] [Back Pages (77K)]

Articles

A study of the total graph in genetic code algebra
Network Biology, 2022, 12(1): 1-10
Birinchi Kumar Boruah, Tazid Ali
[Abstract] [XML] [EndNote] [RefManager] [BibTex] [DOAJ] [PubMed]
[ Full PDF (1157K)]
[Email Article] [Comment/Review Article]

Decoding the characteristics of ORF6 encoded protein of Norway rat Hepatitis E Virus using bioinformatics approach
Network Biology, 2022, 12(1): 11-25
Zoya Shafat, Anwar Ahmed, Mohammad K. Parvez, Shama Parveen
[Abstract] [XML] [EndNote] [RefManager] [BibTex] [DOAJ] [PubMed]
[ Full PDF (1049K)]
[Email Article] [Comment/Review Article]

A mathematical Weibull model altered neuroendocrine control of GH secretion in normal women of advanced reproductive age
Network Biology, 2022, 12(1): 26-31
S. Vijaya, A. Anandan
[Abstract] [XML] [EndNote] [RefManager] [BibTex] [DOAJ] [PubMed]
[ Full PDF (644K)]
[Email Article] [Comment/Review Article]

The growth of DNA databases used to store large number of biological sequence data, has stimulated the importance of alignment of sequences for phylogenetics. Most of the phylogenetic methods based on alignment of sequences consume long time to provide the results. In this regard, a new alignment free measure, based on frequency of occurrence of different nucleotides in sequences has been reported. The Euclidean distance metric has been used over these frequencies of nucleotides to obtain the dissimilarities among DNA sequences. These distances are then used to construct the phylogenetic tree among sequences. In addition, a fuzzy linear programming model has been developed here to construct the phylogenetic network which is considered as the generalized form of phylogenetic tree. As an application, the proposed method is applied over the data set of globin gene of nine species and is validated by comparing the obtained results with the already existing method. The results obtained ...

The growth of DNA databases used to store large number of biological sequence data, has stimulated the importance of alignment of sequences for phylogenetics. Most of the phylogenetic methods based on alignment of sequences consume long time to provide the results. In this regard, a new alignment free measure, based on frequency of occurrence of different nucleotides in sequences has been reported. The Euclidean distance metric has been used over these frequencies of nucleotides to obtain the dissimilarities among DNA sequences. These distances are then used to construct the phylogenetic tree among sequences. In addition, a fuzzy linear programming model has been developed here to construct the phylogenetic network which is considered as the generalized form of phylogenetic tree. As an application, the proposed method is applied over the data set of -globin gene of nine species and is validated by comparing the obtained results with the already existing method. The results obtained...

The growth of DNA databases used to store large number of biological sequence data, has stimulated the importance of alignment of sequences for phylogenetics. Most of the phylogenetic methods based on alignment of sequences consume long time to provide the results. In this regard, a new alignment free measure, based on frequency of occurrence of different nucleotides in sequences has been reported. The Euclidean distance metric has been used over these frequencies of nucleotides to obtain the dissimilarities among DNA sequences. These distances are then used to construct the phylogenetic tree among sequences. In addition, a fuzzy linear programming model has been developed here to construct the phylogenetic network which is considered as the generalized form of phylogenetic tree. As an application, the proposed method is applied over the data set of globin gene of nine species and is validated by comparing the obtained results with the already existing method. The results obtained ...

The involvement of Leptospira spp. in thirty-five (35)
out of fifty (50) cases of swine abortion was
investigated which further required evaluation of
pathogen susceptibility to a panel of antibiotics.
Samples of urine from aborting sows were collected
to recover the pathogen, amplify its 16S rRNA gene
to confirm its identity and monitor cell density in
McFarland Units (MFU) as a measure of
susceptibility to antibiotics. The study permitted the
isolation and evaluation of Leptospira spp.
morphology, demonstration of 3 amplicon products of
the 16S rRNA genes with molecular sizes of 1050 to
1080 bp and identification of 2 Leptospira spp. and L.
hyos after gene sequencing. The susceptibility of the
identified L. hyos to Cephalexin, Neomycin,
Clindamycin, Ciprofloxacin and Sulfamethoxazole
prepared at different concentrations (25 μg, 35 μg and
50 μg) and evaluated after 6 and 12 hour-exposure
time was marked by lower cell densities of recovered
L. hyos relative to the application of higher (35 μg
and 50 μg) antibiotic concentrations. Significant
reduction in cell densities at 12-hr compared to data
obtained on the 6-hour were demonstrated and
underscored the susceptibility of L. hyos as effects of
antibiotic concentration and duration of exposure
time. The bactericidal action of 25 μg Ciprofloxacin;
and 25 and 35 μg Sulfamethoxazole against L. hyos
were established at 6-hour exposure time and that this
bactericidal action was maintained until the 12-hr
with the application of Neomycin and Ciprofloxacin
at 35 and 50 μg and Sulfamethoxazole at 50 μg. These data highlight usefulness of the antibiotics in
the treatment of abortion-associated Leptospira
infections when administered at the concentrations
described.

We show that ranked ohgonucleotide frequencies in both protein-coding and non-coding regions from several genomes fit poorly to the Zipf distribution, but that the same frequency data give excellent fit to the Yule distribution. The parameters of the Yule distribution for oligonucleotide frequencies in exons are the same (within error limits) as the parameters for introns. This precludes application of Yule or Zipf distribution of ranked oligonucleotide frequencies to annotating new genomic sequences.

A maximum entropy principle (MEP) governing the distribution of complexity of short oligonucleotides from large collections of functionally equivalent sequences is presented. The principle is seen to work well in both translated regions (exons and bacterial genes) and introns from various genomes.

The growth of DNA databases used to store large number of biological sequence data, has stimulated the importance of alignment of sequences for phylogenetics. Most of the phylogenetic methods based on alignment of sequences consume long time to provide the results. In this regard, a new alignment free measure, based on frequency of occurrence of different nucleotides in sequences has been reported. The Euclidean distance metric has been used over these frequencies of nucleotides to obtain the dissimilarities among DNA sequences. These distances are then used to construct the phylogenetic tree among sequences. In addition, a fuzzy linear programming model has been developed here to construct the phylogenetic network which is considered as the generalized form of phylogenetic tree. As an application, the proposed method is applied over the data set of -globin gene of nine species and is validated by comparing the obtained results with the already existing method. The results obtained are more promising over the available method and can be applied over any length of input data sequences.

Network Biology
ISSN 2220-8879
CODEN NBEICS
http://www.iaees.org/publications/journals/nb/articles/2019-9(4)/2019-9(4).asp

Volume 9, Number 4, 1 December 2019

Cover Pages
[Front Pages (169K)] [Back Pages (77K)]

Articles

A new measure of dissimilarity and fuzzy linear programming model to construct phylogenetic network among DNA sequences
Network Biology, 2019, 9(4): 78-95
Rinku Mathur, Neeru Adlakha
[Abstract] [XML] [EndNote] [RefManager] [BibTex] [DOAJ] [PubMed]
[ Full PDF (823K)]
[Email Article] [Comment/Review Article]

The evaluation of class 1 to 3 integrons in Salmonella and antimicrobial resistance pattern isolated from Ross 308 broiler chickens
Network Biology, 2019, 9(4): 96-106
Mehrnoosh Doosti Irani, Mostafa Faghani, Abbas Doosti
[Abstract] [XML] [EndNote] [RefManager] [BibTex] [DOAJ] [PubMed]
[ Full PDF (879K)]
[Email Article] [Comment/Review Article]

A maximum entropy principle (MEP) governing the distribution of complexity of short oligonucleotides from large collections of functionally equivalent sequences is presented. The principle is seen to work well in both translated regions (exons and bacterial genes) and introns from various genomes.