KNIndex: a comprehensive database of physicochemical properties for k-tuple nucleotides

Author(s):  
Wen-Ya Zhang ◽  
Junhai Xu ◽  
Jun Wang ◽  
Yuan-Ke Zhou ◽  
Wei Chen ◽  
...  

Abstract With the development of high-throughput sequencing technology, the genomic sequences increased exponentially over the last decade. In order to decode these new genomic data, machine learning methods were introduced for genome annotation and analysis. Due to the requirement of most machines learning methods, the biological sequences must be represented as fixed-length digital vectors. In this representation procedure, the physicochemical properties of k-tuple nucleotides are important information. However, the values of the physicochemical properties of k-tuple nucleotides are scattered in different resources. To facilitate the studies on genomic sequences, we developed the first comprehensive database, namely KNIndex (https://knindex.pufengdu.org), for depositing and visualizing physicochemical properties of k-tuple nucleotides. Currently, the KNIndex database contains 182 properties including one for mononucleotide (DNA), 169 for dinucleotide (147 for DNA and 22 for RNA) and 12 for trinucleotide (DNA). KNIndex database also provides a user-friendly web-based interface for the users to browse, query, visualize and download the physicochemical properties of k-tuple nucleotides. With the built-in conversion and visualization functions, users are allowed to display DNA/RNA sequences as curves of multiple physicochemical properties. We wish that the KNIndex will facilitate the related studies in computational biology.

2021 ◽  
Vol 11 (3) ◽  
pp. 210
Author(s):  
Sumi Elsa John ◽  
Arshad Mohamed Channanath ◽  
Prashantha Hebbar ◽  
Rasheeba Nizam ◽  
Thangavel Alphonse Thanaraj ◽  
...  

With the tremendous advancements in genome sequencing technology in the field of pharmacogenomics, data have to be made accessible to be more efficiently utilized by broader clinical disciplines. Physicians who require the drug–genome interactome information, have been challenged by the complicated pharmacogenomic star-based classification system. We present here an end-to-end web-based pharmacogenomics tool, PharmaKU, which has a comprehensive interface easy-to-use interface. PharmaKU can help to overcome several hurdles posed by previous pharmacogenomics tools, including input in hg38 format only, while hg19/GRCh37 is now the most popular reference genome assembly among clinicians and geneticists, as well as the lack of clinical recommendations and other pertinent dosage-related information. This tool extracts genetic variants from nine well-annotated pharmacogenes (for which diplotype to phenotype information is available) from whole genome variant files and uses Stargazer software to assign diplotypes and apply prescribing recommendations from pharmacogenomic resources. The tool is wrapped with a user-friendly web interface, which allows for choosing hg19 or hg38 as the reference genome version and reports results as a comprehensive PDF document. PharmaKU is anticipated to enable bench to bedside implementation of pharmacogenomics knowledge by bringing precision medicine closer to a clinical reality.


2020 ◽  
Author(s):  
Robson Parmezan Bonidia ◽  
Lucas Dias Hiera Sampaio ◽  
Douglas Silva Domingues ◽  
Alexandre Rossi Paschoal ◽  
Fabrício Martins Lopes ◽  
...  

AbstractThe number of available biological sequences has increased significantly in recent years due to various genomic sequencing projects, creating a huge volume of data. Consequently, new computational methods are needed to analyze and extract information from these sequences. Machine learning methods have shown broad applicability in computational biology and bioinformatics. The utilization of machine learning methods has helped to extract relevant information from various biological datasets. However, there are still several obstacles that motivate new algorithms and pipeline proposals, mainly involving feature extraction problems, in which extracting significant discriminatory information from a biological set is challenging. Considering this, our work proposes to study and analyze a feature extraction pipeline based on mathematical models (Numerical Mapping, Fourier, Entropy, and Complex Networks). As a case study, we analyze Long Non-Coding RNA sequences. Moreover, we divided this work into two studies, e.g., (I) we assessed our proposal with the most addressed problem in our review, e.g., lncRNA vs. mRNA; (II) we tested its generalization on different classification problems, e.g., circRNA vs. lncRNA. The experimental results demonstrated three main contributions: (1) An in-depth study of several mathematical models; (2) a new feature extraction pipeline and (3) its generalization and robustness for distinct biological sequence classification.


2019 ◽  
Vol 47 (W1) ◽  
pp. W632-W635 ◽  
Author(s):  
Lukas Bartonek ◽  
Bojan Zagrovic

Abstract The structure, dynamics and, ultimately, biological function of proteins and nucleic acids are determined by the physicochemical properties of their primary sequences. Such properties are frequently captured via one-dimensional profile plots depicting a given physicochemical variable as a function of sequence position. Hydrophobicity, charge or structural disorder in proteins or nucleobase-density in nucleic acids are routinely visualized in this manner to analyze sequences at a glance. Such visualizations, however, are typically created case-by-case in a purely static manner, employ fixed visualization parameters only and do not enable a quantitative comparison between different sequences. Here, we present VOLPES (volpes.univie.ac.at), a user-friendly web server and the corresponding JavaScript library that enable a fully interactive, multifunctional visualization, analysis and comparison of the physicochemical properties of protein and nucleic-acid sequences, allowing unprecedented insight into biological sequence data and creating a starting point for further in-depth exploration.


2017 ◽  
Vol 1 (1) ◽  
pp. 44-49
Author(s):  
Nur Azizah ◽  
Dedeh Supriyanti ◽  
Siti Fairuz Aminah Mustapha ◽  
Holly Yang

In a company, the process of income and expense of money must have a profit-generating goal base. The success of financial management within the company, can be monitored from the ability of the financial management in managing the finances and utilize all the opportunities that exist with as much as possible with the aim to control the company's cash (cash flow) and the impact of generating profits in accordance with expectations. With a web-based online accounting system version 2.0, companies can be given the ease to manage money in and out of the company's cash. It has a user friendly system with navigation that makes it easy for the financial management to use it. Starting from the creation of a company's cash account used as a cash account and corporate bank account on the system, deletion or filing of cash accounts, up to the transfer invoice creation feature, receive and send money. Thus, this system is very effective and efficient in the management of income and corporate cash disbursements.   Keywords:​Accounting Online System, Financial Management, Cash and Bank


2018 ◽  
Vol 3 (1) ◽  
Author(s):  
Mehmet EMIN KORTAK

This research aimed at designing and improving the web-based integrated peer and self- assessment. WesPASS (web-based peer-assessment system), developed in this research, allows students to assess their own or their peers’ performance and project assignments and to report about the result of these assessments so that they correct their assignments. This study employed design-based research. The participants included 102 fourth grade primary school students and their 4 teachers from 2 state and 2 private primary schools in Ankara, Kecioren (Turkey) who employed the system and were engaged in a questionnaire survey to assess its quality. The findings were analyzed through quantitative data analysis. The findings revealed that the system can be used by elementary school students for peer and self-assessment system. The participants stated that WesPASS is simple and user-friendly, and it accelerates the assessment process by employing information technology and allows to share opinions 


2021 ◽  
Vol 22 (S2) ◽  
Author(s):  
Daniele D’Agostino ◽  
Pietro Liò ◽  
Marco Aldinucci ◽  
Ivan Merelli

Abstract Background High-throughput sequencing Chromosome Conformation Capture (Hi-C) allows the study of DNA interactions and 3D chromosome folding at the genome-wide scale. Usually, these data are represented as matrices describing the binary contacts among the different chromosome regions. On the other hand, a graph-based representation can be advantageous to describe the complex topology achieved by the DNA in the nucleus of eukaryotic cells. Methods Here we discuss the use of a graph database for storing and analysing data achieved by performing Hi-C experiments. The main issue is the size of the produced data and, working with a graph-based representation, the consequent necessity of adequately managing a large number of edges (contacts) connecting nodes (genes), which represents the sources of information. For this, currently available graph visualisation tools and libraries fall short with Hi-C data. The use of graph databases, instead, supports both the analysis and the visualisation of the spatial pattern present in Hi-C data, in particular for comparing different experiments or for re-mapping omics data in a space-aware context efficiently. In particular, the possibility of describing graphs through statistical indicators and, even more, the capability of correlating them through statistical distributions allows highlighting similarities and differences among different Hi-C experiments, in different cell conditions or different cell types. Results These concepts have been implemented in NeoHiC, an open-source and user-friendly web application for the progressive visualisation and analysis of Hi-C networks based on the use of the Neo4j graph database (version 3.5). Conclusion With the accumulation of more experiments, the tool will provide invaluable support to compare neighbours of genes across experiments and conditions, helping in highlighting changes in functional domains and identifying new co-organised genomic compartments.


Metabolites ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 113
Author(s):  
Julia Koblitz ◽  
Sabine Will ◽  
S. Riemer ◽  
Thomas Ulas ◽  
Meina Neumann-Schaal ◽  
...  

Genome-scale metabolic models are of high interest in a number of different research fields. Flux balance analysis (FBA) and other mathematical methods allow the prediction of the steady-state behavior of metabolic networks under different environmental conditions. However, many existing applications for flux optimizations do not provide a metabolite-centric view on fluxes. Metano is a standalone, open-source toolbox for the analysis and refinement of metabolic models. While flux distributions in metabolic networks are predominantly analyzed from a reaction-centric point of view, the Metano methods of split-ratio analysis and metabolite flux minimization also allow a metabolite-centric view on flux distributions. In addition, we present MMTB (Metano Modeling Toolbox), a web-based toolbox for metabolic modeling including a user-friendly interface to Metano methods. MMTB assists during bottom-up construction of metabolic models by integrating reaction and enzymatic annotation data from different databases. Furthermore, MMTB is especially designed for non-experienced users by providing an intuitive interface to the most commonly used modeling methods and offering novel visualizations. Additionally, MMTB allows users to upload their models, which can in turn be explored and analyzed by the community. We introduce MMTB by two use cases, involving a published model of Corynebacterium glutamicum and a newly created model of Phaeobacter inhibens.


2021 ◽  
pp. 193229682098557
Author(s):  
Alysha M. De Livera ◽  
Jonathan E. Shaw ◽  
Neale Cohen ◽  
Anne Reutens ◽  
Agus Salim

Motivation: Continuous glucose monitoring (CGM) systems are an essential part of novel technology in diabetes management and care. CGM studies have become increasingly popular among researchers, healthcare professionals, and people with diabetes due to the large amount of useful information that can be collected using CGM systems. The analysis of the data from these studies for research purposes, however, remains a challenge due to the characteristics and large volume of the data. Results: Currently, there are no publicly available interactive software applications that can perform statistical analyses and visualization of data from CGM studies. With the rapidly increasing popularity of CGM studies, such an application is becoming necessary for anyone who works with these large CGM datasets, in particular for those with little background in programming or statistics. CGMStatsAnalyser is a publicly available, user-friendly, web-based application, which can be used to interactively visualize, summarize, and statistically analyze voluminous and complex CGM datasets together with the subject characteristics with ease.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hongwei Yan ◽  
Qi Liu ◽  
Jieming Jiang ◽  
Xufang Shen ◽  
Lei Zhang ◽  
...  

AbstractAlthough sex determination and differentiation are key developmental processes in animals, the involvement of non-coding RNA in the regulation of this process is still not clarified. The tiger pufferfish (Takifugu rubripes) is one of the most economically important marine cultured species in Asia, but analyses of miRNA and long non-coding RNA (lncRNA) at early sex differentiation stages have not been conducted yet. In our study, high-throughput sequencing technology was used to sequence transcriptome libraries from undifferentiated gonads of T. rubripes. In total, 231 (107 conserved, and 124 novel) miRNAs were obtained, while 2774 (523 conserved, and 2251 novel) lncRNAs were identified. Of these, several miRNAs and lncRNAs were predicted to be the regulators of the expression of sex-related genes (including fru-miR-15b/foxl2, novel-167, novel-318, and novel-538/dmrt1, novel-548/amh, lnc_000338, lnc_000690, lnc_000370, XLOC_021951, and XR_965485.1/gsdf). Analysis of differentially expressed miRNAs and lncRNAs showed that three mature miRNAs up-regulated and five mature miRNAs were down-regulated in male gonads compared to female gonads, while 79 lncRNAs were up-regulated and 51 were down-regulated. These findings could highlight a group of interesting miRNAs and lncRNAs for future studies and may reveal new insights into the function of miRNAs and lncRNAs in sex determination and differentiation.


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