scholarly journals The DNA walk and its demonstration of deterministic chaos—relevance to genomic alterations in lung cancer

2019 ◽  
Vol 35 (16) ◽  
pp. 2738-2748 ◽  
Author(s):  
Blake Hewelt ◽  
Haiqing Li ◽  
Mohit Kumar Jolly ◽  
Prakash Kulkarni ◽  
Isa Mambetsariev ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Open Source ◽  
Fractal Analysis ◽  
Dna Sequences ◽  
Chaotic Behavior ◽  
Supplementary Information ◽  
Wild Type ◽  
Genomic Alterations ◽  
Turtle Graphics ◽  
Dna Walk

AbstractMotivationAdvancements in cancer genetics have facilitated the development of therapies with actionable mutations. Although mutated genes have been studied extensively, their chaotic behavior has not been appreciated. Thus, in contrast to naïve DNA, mutated DNA sequences can display characteristics of unpredictability and sensitivity to the initial conditions that may be dictated by the environment, expression patterns and presence of other genomic alterations. Employing a DNA walk as a form of 2D analysis of the nucleotide sequence, we demonstrate that chaotic behavior in the sequence of a mutated gene can be predicted.ResultsUsing fractal analysis for these DNA walks, we have determined the complexity and nucleotide variance of commonly observed mutated genes in non-small cell lung cancer, and their wild-type counterparts. DNA walks for wild-type genes demonstrate varying levels of chaos, with BRAF, NTRK1 and MET exhibiting greater levels of chaos than KRAS, paxillin and EGFR. Analyzing changes in chaotic properties, such as changes in periodicity and linearity, reveal that while deletion mutations indicate a notable disruption in fractal ‘self-similarity’, fusion mutations demonstrate bifurcations between the two genes. Our results suggest that the fractals generated by DNA walks can yield important insights into potential consequences of these mutated genes.Availability and implementationIntroduction to Turtle graphics in Python is an open source article on learning to develop a script for Turtle graphics in Python, freely available on the web at https://docs.python.org/2/library/turtle.html. cDNA sequences were obtained through NCBI RefSeq database, an open source database that contains information on a large array of genes, such as their nucleotide and amino acid sequences, freely available at https://www.ncbi.nlm.nih.gov/refseq/. FracLac plugin for Fractal analysis in ImageJ is an open source plugin for the ImageJ program to perform fractal analysis, free to download at https://imagej.nih.gov/ij/plugins/fraclac/FLHelp/Introduction.html.Supplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals Diagnosis of Lung Cancer by Fractal Analysis of Damaged DNA

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Hamidreza Namazi ◽  
Mona Kiminezhadmalaie
Keyword(s):  
Lung Cancer ◽  
Dna Sequences ◽  
Hurst Exponent ◽  
The Body ◽  
Cancer Genes ◽  
A Genome ◽  
Different Types ◽  
Diagnosis Of Lung Cancer ◽  
Dna Walk ◽  
Damaged Dna

Cancer starts when cells in a part of the body start to grow out of control. In fact cells become cancer cells because of DNA damage. A DNA walk of a genome represents how the frequency of each nucleotide of a pairing nucleotide couple changes locally. In this research in order to study the cancer genes, DNA walk plots of genomes of patients with lung cancer were generated using a program written in MATLAB language. The data so obtained was checked for fractal property by computing the fractal dimension using a program written in MATLAB. Also, the correlation of damaged DNA was studied using the Hurst exponent measure. We have found that the damaged DNA sequences are exhibiting higher degree of fractality and less correlation compared with normal DNA sequences. So we confirmed this method can be used for early detection of lung cancer. The method introduced in this research not only is useful for diagnosis of lung cancer but also can be applied for detection and growth analysis of different types of cancers.

scholarly journals Nucleotide Archival Format (NAF) enables efficient lossless reference-free compression of DNA sequences

2019 ◽  
Vol 35 (19) ◽  
pp. 3826-3828 ◽  
Author(s):  
Kirill Kryukov ◽  
Mahoko Takahashi Ueda ◽  
So Nakagawa ◽  
Tadashi Imanishi
Keyword(s):  
Open Source ◽  
Dna Sequence ◽  
Compression Ratio ◽  
Dna Sequences ◽  
General Purpose ◽  
Supplementary Information ◽  
File Format ◽  
Storage Space ◽  
Supplementary Data ◽  
Network Transmission

Abstract Summary DNA sequence databases use compression such as gzip to reduce the required storage space and network transmission time. We describe Nucleotide Archival Format (NAF)—a new file format for lossless reference-free compression of FASTA and FASTQ-formatted nucleotide sequences. Nucleotide Archival Format compression ratio is comparable to the best DNA compressors, while providing dramatically faster decompression. We compared our format with DNA compressors: DELIMINATE and MFCompress, and with general purpose compressors: gzip, bzip2, xz, brotli and zstd. Availability and implementation NAF compressor and decompressor, as well as format specification are available at https://github.com/KirillKryukov/naf. Format specification is in public domain. Compressor and decompressor are open source under the zlib/libpng license, free for nearly any use. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals MLDSP-GUI: an alignment-free standalone tool with an interactive graphical user interface for DNA sequence comparison and analysis

2019 ◽  
Vol 36 (7) ◽  
pp. 2258-2259 ◽  
Author(s):  
Gurjit S Randhawa ◽  
Kathleen A Hill ◽  
Lila Kari
Keyword(s):  
User Interface ◽  
Open Source ◽  
Graphical User Interface ◽  
Dna Sequences ◽  
Software Tool ◽  
Digital Signal ◽  
Disease Classification ◽  
Supplementary Information ◽  
Alignment Free ◽  
Comparison And Analysis

Abstract Summary Machine Learning with Digital Signal Processing and Graphical User Interface (MLDSP-GUI) is an open-source, alignment-free, ultrafast, computationally lightweight, and standalone software tool with an interactive GUI for comparison and analysis of DNA sequences. MLDSP-GUI is a general-purpose tool that can be used for a variety of applications such as taxonomic classification, disease classification, virus subtype classification, evolutionary analyses, among others. Availability and implementation MLDSP-GUI is open-source, cross-platform compatible, and is available under the terms of the Creative Commons Attribution 4.0 International license (http://creativecommons.org/licenses/by/4.0/). The executable and dataset files are available at https://sourceforge.net/projects/mldsp-gui/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals MLDSP-GUI: An alignment-free standalone tool with an interactive graphical user interface for DNA sequence comparison and analysis

2019 ◽  
Author(s):  
Gurjit S. Randhawa ◽  
Kathleen A. Hill ◽  
Lila Kari
Keyword(s):  
User Interface ◽  
Open Source ◽  
Graphical User Interface ◽  
Dna Sequences ◽  
Disease Classification ◽  
Supplementary Information ◽  
Link Type ◽  
Alignment Free ◽  
Comparison And Analysis ◽  
Interactive Graphical User Interface

AbstractSummaryMLDSP-GUI (Machine Learning with Digital Signal Processing) is an open-source, alignment-free, ultrafast, computationally lightweight, standalone software tool with an interactive Graphical User Interface (GUI) for comparison and analysis of DNA sequences. MLDSP-GUI is a general-purpose tool that can be used for a variety of applications such as taxonomic classification, disease classification, virus subtype classification, evolutionary analyses, among others.AvailabilityMLDSP-GUI is open-source, cross-platform compatible, and is available under the terms of the Creative Commons Attribution 4.0 International license (http://creativecommons.org/licenses/by/4.0/). The executable and dataset files are available at https://sourceforge.net/projects/mldsp-gui/[email protected] informationSupplementary data are available online.

A Case of EGFR-wild-type Adenocarcinoma of Recurrent Non-small Cell Lung Cancer Responding to Erlotinib

Haigan ◽  
2012 ◽  
Vol 52 (3) ◽  
pp. 315-319
Author(s):  
Masami Morimoto ◽  
Naoki Hino ◽  
Hisashi Matsuoka ◽  
Takanori Miyoshi ◽  
Masaru Tsuyuguchi
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Wild Type ◽  
Small Cell Lung

scholarly journals ccNetViz: a WebGL-based JavaScript library for visualization of large networks

2020 ◽  
Vol 36 (16) ◽  
pp. 4527-4529
Author(s):  
Ales Saska ◽  
David Tichy ◽  
Robert Moore ◽  
Achilles Rasquinha ◽  
Caner Akdas ◽  
...  
Keyword(s):  
Systems Biology ◽  
Complex Networks ◽  
Open Source ◽  
High Speed ◽  
A Priori ◽  
Supplementary Information ◽  
Network Visualization ◽  
Supplementary Data ◽  
Web Based ◽  
Flow Of Information

Abstract Summary Visualizing a network provides a concise and practical understanding of the information it represents. Open-source web-based libraries help accelerate the creation of biologically based networks and their use. ccNetViz is an open-source, high speed and lightweight JavaScript library for visualization of large and complex networks. It implements customization and analytical features for easy network interpretation. These features include edge and node animations, which illustrate the flow of information through a network as well as node statistics. Properties can be defined a priori or dynamically imported from models and simulations. ccNetViz is thus a network visualization library particularly suited for systems biology. Availability and implementation The ccNetViz library, demos and documentation are freely available at http://helikarlab.github.io/ccNetViz/. Supplementary information Supplementary data are available at Bioinformatics online.

Developing a Genetic System in Deinococcus radiodurans for Analyzing Mutations

Genetics ◽  
2004 ◽  
Vol 166 (2) ◽  
pp. 661-668
Author(s):  
Mandy Kim ◽  
Erika Wolff ◽  
Tiffany Huang ◽  
Lilit Garibyan ◽  
Ashlee M Earl ◽  
...  
Keyword(s):  
Dna Sequences ◽  
Deinococcus Radiodurans ◽  
Genetic System ◽  
Base Change ◽  
Base Substitution ◽  
Wild Type ◽  
Base Pairs ◽  
E Coli ◽  
Radiation Induced ◽  
Induced Mutagenesis

Abstract We have applied a genetic system for analyzing mutations in Escherichia coli to Deinococcus radiodurans, an extremeophile with an astonishingly high resistance to UV- and ionizing-radiation-induced mutagenesis. Taking advantage of the conservation of the β-subunit of RNA polymerase among most prokaryotes, we derived again in D. radiodurans the rpoB/Rif r system that we developed in E. coli to monitor base substitutions, defining 33 base change substitutions at 22 different base pairs. We sequenced >250 mutations leading to Rif r in D. radiodurans derived spontaneously in wild-type and uvrD (mismatch-repair-deficient) backgrounds and after treatment with N-methyl-N′-nitro-N-nitrosoguanidine (NTG) and 5-azacytidine (5AZ). The specificities of NTG and 5AZ in D. radiodurans are the same as those found for E. coli and other organisms. There are prominent base substitution hotspots in rpoB in both D. radiodurans and E. coli. In several cases these are at different points in each organism, even though the DNA sequences surrounding the hotspots and their corresponding sites are very similar in both D. radiodurans and E. coli. In one case the hotspots occur at the same site in both organisms.

scholarly journals DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome

2021 ◽  
Author(s):  
Yanrong Ji ◽  
Zhihan Zhou ◽  
Han Liu ◽  
Ramana V Davuluri
Keyword(s):  
Dna Sequences ◽  
Regulatory Elements ◽  
Ease Of Use ◽  
Fine Tuning ◽  
Supplementary Information ◽  
Sequence Motifs ◽  
Semantic Relationship ◽  
Accurate Identification ◽  
Conserved Sequence ◽  
Genome Wide

Abstract Motivation Deciphering the language of non-coding DNA is one of the fundamental problems in genome research. Gene regulatory code is highly complex due to the existence of polysemy and distant semantic relationship, which previous informatics methods often fail to capture especially in data-scarce scenarios. Results To address this challenge, we developed a novel pre-trained bidirectional encoder representation, named DNABERT, to capture global and transferrable understanding of genomic DNA sequences based on up and downstream nucleotide contexts. We compared DNABERT to the most widely used programs for genome-wide regulatory elements prediction and demonstrate its ease of use, accuracy and efficiency. We show that the single pre-trained transformers model can simultaneously achieve state-of-the-art performance on prediction of promoters, splice sites and transcription factor binding sites, after easy fine-tuning using small task-specific labeled data. Further, DNABERT enables direct visualization of nucleotide-level importance and semantic relationship within input sequences for better interpretability and accurate identification of conserved sequence motifs and functional genetic variant candidates. Finally, we demonstrate that pre-trained DNABERT with human genome can even be readily applied to other organisms with exceptional performance. We anticipate that the pre-trained DNABERT model can be fined tuned to many other sequence analyses tasks. Availability and implementation The source code, pretrained and finetuned model for DNABERT are available at GitHub (https://github.com/jerryji1993/DNABERT). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Suberoylanilide hydroxamic acid enhances the radiosensitivity of lung cancer cells through acetylated wild-type and mutant p53-dependent modulation of mitochondrial apoptosis

2021 ◽  
Vol 49 (2) ◽  
pp. 030006052098154
Author(s):  
Kan Wu ◽  
Xueqin Chen ◽  
Xufeng Chen ◽  
Shirong Zhang ◽  
Yasi Xu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Cells ◽  
Hydroxamic Acid ◽  
Site Directed Mutagenesis ◽  
Lung Cancer Cells ◽  
Mutant P53 ◽  
Suberoylanilide Hydroxamic Acid ◽  
Mitochondrial Apoptosis ◽  
Wild Type ◽  
Clonogenic Cell

Objective Suberoylanilide hydroxamic acid (SAHA), a histone deacetylase inhibitor, has shown potential as a candidate radiosensitizer for many types of cancers. This study aimed to explore the radiosensitization mechanism of SAHA in lung cancer cells. Methods Mutations in p53 were generated by site-directed mutagenesis using polymerase chain reaction. Transfection was performed to generate H1299 cells carrying wild-type or mutant p53. The radiosensitizing enhancement ratio was determined by clonogenic assays. Mitochondrial apoptosis was detected using JC-1 staining and flow cytometry analysis. Results Our results showed that SAHA induced radiosensitization in H1299 cells expressing wild-type p53, p53R175H or p53P223L, but this enhanced clonogenic cell death was not observed in parental H1299 (p53-null) cells or H1299 cells expressing p53 with K120R, A161T and V274R mutations. In SAHA-sensitized cells, mitochondrial apoptosis was induced following exposure to irradiation. Additionally, we observed that a secondary mutation at K120 (K120R) could eliminate p53-mediated radiosensitization and mitochondrial apoptosis. Conclusions The results of this study suggest that wild-type and specific mutant forms of p53 mediate SAHA-induced radiosensitization by regulating mitochondrial apoptosis, and the stabilization of K120 acetylation by SAHA is the molecular basis contributing to radiosensitization in lung cancer cells.

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