scholarly journals CoV-Seq, a New Tool for SARS-CoV-2 Genome Analysis and Visualization: Development and Usability Study

10.2196/22299 ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. e22299
Author(s):  
Boxiang Liu ◽  
Kaibo Liu ◽  
He Zhang ◽  
Liang Zhang ◽  
Yuchen Bian ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Ad Hoc ◽  
Web Server ◽  
Data Sets ◽  
Global Pandemic ◽  
Global Initiative ◽  
Public Repositories ◽  
Downstream Analysis ◽  
Programming Knowledge ◽  
The Web

Background COVID-19 became a global pandemic not long after its identification in late 2019. The genomes of SARS-CoV-2 are being rapidly sequenced and shared on public repositories. To keep up with these updates, scientists need to frequently refresh and reclean data sets, which is an ad hoc and labor-intensive process. Further, scientists with limited bioinformatics or programming knowledge may find it difficult to analyze SARS-CoV-2 genomes. Objective To address these challenges, we developed CoV-Seq, an integrated web server that enables simple and rapid analysis of SARS-CoV-2 genomes. Methods CoV-Seq is implemented in Python and JavaScript. The web server and source code URLs are provided in this article. Results Given a new sequence, CoV-Seq automatically predicts gene boundaries and identifies genetic variants, which are displayed in an interactive genome visualizer and are downloadable for further analysis. A command-line interface is available for high-throughput processing. In addition, we aggregated all publicly available SARS-CoV-2 sequences from the Global Initiative on Sharing Avian Influenza Data (GISAID), National Center for Biotechnology Information (NCBI), European Nucleotide Archive (ENA), and China National GeneBank (CNGB), and extracted genetic variants from these sequences for download and downstream analysis. The CoV-Seq database is updated weekly. Conclusions We have developed CoV-Seq, an integrated web service for fast and easy analysis of custom SARS-CoV-2 sequences. The web server provides an interactive module for the analysis of custom sequences and a weekly updated database of genetic variants of all publicly accessible SARS-CoV-2 sequences. We believe CoV-Seq will help improve our understanding of the genetic underpinnings of COVID-19.

scholarly journals CoV-Seq, a New Tool for SARS-CoV-2 Genome Analysis and Visualization: Development and Usability Study (Preprint)

2020 ◽  
Author(s):  
Boxiang Liu ◽  
Kaibo Liu ◽  
He Zhang ◽  
Liang Zhang ◽  
Yuchen Bian ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Ad Hoc ◽  
Web Server ◽  
Data Sets ◽  
Global Pandemic ◽  
Global Initiative ◽  
Public Repositories ◽  
Downstream Analysis ◽  
Programming Knowledge ◽  
The Web

BACKGROUND COVID-19 became a global pandemic not long after its identification in late 2019. The genomes of SARS-CoV-2 are being rapidly sequenced and shared on public repositories. To keep up with these updates, scientists need to frequently refresh and reclean data sets, which is an ad hoc and labor-intensive process. Further, scientists with limited bioinformatics or programming knowledge may find it difficult to analyze SARS-CoV-2 genomes. OBJECTIVE To address these challenges, we developed CoV-Seq, an integrated web server that enables simple and rapid analysis of SARS-CoV-2 genomes. METHODS CoV-Seq is implemented in Python and JavaScript. The web server and source code URLs are provided in this article. RESULTS Given a new sequence, CoV-Seq automatically predicts gene boundaries and identifies genetic variants, which are displayed in an interactive genome visualizer and are downloadable for further analysis. A command-line interface is available for high-throughput processing. In addition, we aggregated all publicly available SARS-CoV-2 sequences from the Global Initiative on Sharing Avian Influenza Data (GISAID), National Center for Biotechnology Information (NCBI), European Nucleotide Archive (ENA), and China National GeneBank (CNGB), and extracted genetic variants from these sequences for download and downstream analysis. The CoV-Seq database is updated weekly. CONCLUSIONS We have developed CoV-Seq, an integrated web service for fast and easy analysis of custom SARS-CoV-2 sequences. The web server provides an interactive module for the analysis of custom sequences and a weekly updated database of genetic variants of all publicly accessible SARS-CoV-2 sequences. We believe CoV-Seq will help improve our understanding of the genetic underpinnings of COVID-19.

scholarly journals CoV-Seq: SARS-CoV-2 Genome Analysis and Visualization

2020 ◽  
Author(s):  
Boxiang Liu ◽  
Kaibo Liu ◽  
He Zhang ◽  
Liang Zhang ◽  
Yuchen Bian ◽  
...  
Keyword(s):  
Ad Hoc ◽  
Rapid Analysis ◽  
Supplementary Information ◽  
Command Line ◽  
Command Line Interface ◽  
Link Type ◽  
Global Pandemic ◽  
Fast Pace ◽  
Public Repositories ◽  
Programming Knowledge

AbstractSummaryCOVID-19 has become a global pandemic not long after its inception in late 2019. SARS-CoV-2 genomes are being sequenced and shared on public repositories at a fast pace. To keep up with these updates, scientists need to frequently refresh and reclean datasets, which is ad hoc and labor-intensive. Further, scientists with limited bioinformatics or programming knowledge may find it difficult to analyze SARS-CoV-2 genomes. In order to address these challenges, we developed CoV-Seq, a webserver to enable simple and rapid analysis of SARS-CoV-2 genomes. Given a new sequence, CoV-Seq automatically predicts gene boundaries and identifies genetic variants, which are presented in an interactive genome visualizer and are downloadable for further analysis. A command-line interface is also available for high-throughput processing.Availability and ImplementationCoV-Seq is implemented in Python and Javascript. The webserver is available at http://covseq.baidu.com/ and the source code is available from https://github.com/boxiangliu/[email protected] informationSupplementary information are available at bioRxiv online.

scholarly journals Lightron : A GUI Integrated, Rust Based Web Server

2021 ◽  
pp. 554-560
Author(s):  
Apurva Solanki ◽  
Aryan Parekh ◽  
Gaurav Chawda ◽  
Mrs. Geetha S.
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Web Server ◽  
The Internet ◽  
Web Servers ◽  
The Past ◽  
Global Pandemic ◽  
Day By Day ◽  
The Web

Day by day, the number of users are increasing on the internet and the web servers need to cater to the requests constantly, also if compared to the past years this year, due to a global pandemic and lockdown in various countries, the requests on the web have surged exponentially. The complexity of configuring a web server is also increasing as the development continues. In this paper, we propose a Lightron web server, which is highly scalable and can cater many requests at a time. Additionally, to ease users from the configuration of the web server we introduced Graphical User Interface which is beginner friendly.

3MCor: An Integrative Web Server for Metabolome-Microbiome-Metadata Correlation Analysis

2021 ◽  
Author(s):  
Tao Sun ◽  
Mengci Li ◽  
Xiangtian Yu ◽  
Dandan Liang ◽  
Guoxiang Xie ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Web Server ◽  
Public Library ◽  
Rapid Identification ◽  
Data Sets ◽  
Real World Data ◽  
Continuous Phenotype ◽  
Flexible Operation ◽  
Key Nodes ◽  
The Web

Abstract Background: Mounting evidences have shown that microbiome and metabolome are closely linked to human health and dual-omics studies expanded our knowledge and understanding of health and life. Here, we designed and developed a full-function and easy-to-use platform, 3MCor (http://3mcor.cn/), for metabolome and microbiome correlation analysis under the instruction of phenotype and with the consideration of confounders.Results: Many traditional and newly reported correlation analysis methods were integrated for intra- and inter-correlation analysis. Three inter-correlation pipelines are provided for global, hierarchical, and pairwise analysis. Especially, the incorporated network analysis function is conducive to a rapid identification of network clusters and key nodes from a complicated correlation network. Complete numerical results (csv files) and rich figures (pdf files) will be generated in minutes. To our knowledge, 3MCor is the first platform developed specifically for the correlation analysis of metabolome and microbiome. Its functions were compared with corresponding modules of existing omics data analysis platforms. Results from 2 real-world data sets, one from a public library with a continuous phenotype and one from our lab with a categorical phenotype, were used to demonstrate its simple and flexible operation, comprehensive outputs, and distinctive contribution to dual-omics studies. Conclusions: 3MCor is powerful with complementary pipelines and comprehensive considerations of phenotypes, confounders, and the interactions among omics features. In addition to the web server, the backend R script is available at https://github.com/chentianlu/3MCorServer.

APLIKASI PENCARI INFORMASI PERMINTAAN LAYANAN WEB YANG ERROR MENGGUNAKAN ALGORITMA BOYER-MOORE

2016 ◽  
Vol 1 (1) ◽  
pp. 001
Author(s):  
Harry Setya Hadi
Keyword(s):  
Data Storage ◽  
Computer Network ◽  
Web Server ◽  
Access Methods ◽  
Ip Address ◽  
String Searching ◽  
Common Process ◽  
Web Server Logs ◽  
Different Parts ◽  
The Web

String searching is a common process in the processes that made the computer because the text is the main form of data storage. Boyer-Moore is the search string from right to left is considered the most efficient methods in practice, and matching string from the specified direction specifically an algorithm that has the best results theoretically. A system that is connected to a computer network that literally pick a web server that is accessed by multiple users in different parts of both good and bad aim. Any activity performed by the user, will be stored in Web server logs. With a log report contained in the web server can help a web server administrator to search the web request error. Web server log is a record of the activities of a web site that contains the data associated with the IP address, time of access, the page is opened, activities, and access methods. The amount of data contained in the resulting log is a log shed useful information.

scholarly journals PathFinder: Bayesian inference of clone migration histories in cancer

2020 ◽  
Vol 36 (Supplement_2) ◽  
pp. i675-i683
Author(s):  
Sudhir Kumar ◽  
Antonia Chroni ◽  
Koichiro Tamura ◽  
Maxwell Sanderford ◽  
Olumide Oladeinde ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Cancer Cells ◽  
Bayesian Approach ◽  
Genetic Variants ◽  
Cancer Development ◽  
Posterior Probabilities ◽  
Migration Routes ◽  
Primary Tumors ◽  
History Of ◽  
The Web

Abstract Summary Metastases cause a vast majority of cancer morbidity and mortality. Metastatic clones are formed by dispersal of cancer cells to secondary tissues, and are not medically detected or visible until later stages of cancer development. Clone phylogenies within patients provide a means of tracing the otherwise inaccessible dynamic history of migrations of cancer cells. Here, we present a new Bayesian approach, PathFinder, for reconstructing the routes of cancer cell migrations. PathFinder uses the clone phylogeny, the number of mutational differences among clones, and the information on the presence and absence of observed clones in primary and metastatic tumors. By analyzing simulated datasets, we found that PathFinder performes well in reconstructing clone migrations from the primary tumor to new metastases as well as between metastases. It was more challenging to trace migrations from metastases back to primary tumors. We found that a vast majority of errors can be corrected by sampling more clones per tumor, and by increasing the number of genetic variants assayed per clone. We also identified situations in which phylogenetic approaches alone are not sufficient to reconstruct migration routes. In conclusion, we anticipate that the use of PathFinder will enable a more reliable inference of migration histories and their posterior probabilities, which is required to assess the relative preponderance of seeding of new metastasis by clones from primary tumors and/or existing metastases. Availability and implementation PathFinder is available on the web at https://github.com/SayakaMiura/PathFinder.

scholarly journals Experiments of Image Classification Using Dissimilarity Spaces Built with Siamese Networks

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1573
Author(s):  
Loris Nanni ◽  
Giovanni Minchio ◽  
Sheryl Brahnam ◽  
Gianluca Maguolo ◽  
Alessandra Lumini
Keyword(s):  
Vector Space ◽  
Image Classification ◽  
Ad Hoc ◽  
Feature Space ◽  
Medical Data ◽  
Training Data ◽  
Data Sets ◽  
Large Set ◽  
Clustering Methods ◽  
Siamese Networks

Traditionally, classifiers are trained to predict patterns within a feature space. The image classification system presented here trains classifiers to predict patterns within a vector space by combining the dissimilarity spaces generated by a large set of Siamese Neural Networks (SNNs). A set of centroids from the patterns in the training data sets is calculated with supervised k-means clustering. The centroids are used to generate the dissimilarity space via the Siamese networks. The vector space descriptors are extracted by projecting patterns onto the similarity spaces, and SVMs classify an image by its dissimilarity vector. The versatility of the proposed approach in image classification is demonstrated by evaluating the system on different types of images across two domains: two medical data sets and two animal audio data sets with vocalizations represented as images (spectrograms). Results show that the proposed system’s performance competes competitively against the best-performing methods in the literature, obtaining state-of-the-art performance on one of the medical data sets, and does so without ad-hoc optimization of the clustering methods on the tested data sets.

SSMBS: a web server to locate sequentially separated motifs in biological sequences

2009 ◽  
Vol 43 (1) ◽  
pp. 203-205 ◽  
Author(s):  
Chetan Kumar ◽  
K. Sekar
Keyword(s):  
Amino Acids ◽  
Web Server ◽  
Nucleotide Sequences ◽  
Regular Expressions ◽  
Biological Sequences ◽  
Sequence Motifs ◽  
Specific Order ◽  
The Web

The identification of sequence (amino acids or nucleotides) motifs in a particular order in biological sequences has proved to be of interest. This paper describes a computing server,SSMBS, which can locate and display the occurrences of user-defined biologically important sequence motifs (a maximum of five) present in a specific order in protein and nucleotide sequences. While the server can efficiently locate motifs specified using regular expressions, it can also find occurrences of long and complex motifs. The computation is carried out by an algorithm developed using the concepts of quantifiers in regular expressions. The web server is available to users around the clock at http://dicsoft1.physics.iisc.ernet.in/ssmbs/.

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