scholarly journals iCn3D: from Web-based 3D Viewer to Structure Analysis Tool in Batch Mode

2021 ◽  
Author(s):  
Jiyao Wang ◽  
Philippe Youkharibache ◽  
Aron Marchler-Bauer ◽  
Christopher Lanczycki ◽  
Dachuan Zhang ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Large Data ◽  
Accessible Surface Area ◽  
Solvent Accessible Surface Area ◽  
Analysis Tool ◽  
Batch Mode ◽  
Data Set ◽  
Web Based ◽  
Protein Protein Interaction ◽  
Link Type

AbstractiCn3D was originally released as a web-based 3D viewer, which allows users to create a custom view in a life-long, shortened URL to share with colleagues. Recently, iCn3D was converted to use JavaScript classes and could be used as a library to write Node.js scripts. Any interactive features in iCn3D can be converted to Node.js scripts to run in batch mode for a large data set. Currently the following Node.js script examples are available at https://github.com/ncbi/icn3d/tree/master/icn3dnode: ligand-protein interaction, protein-protein interaction, change of interactions due to residue mutations, DelPhi electrostatic potential, and solvent accessible surface area. iCn3D PNG images can also be exported in batch mode using a Python script. Other recent features of iCn3D include the alignment of multiple chains from different structures, realignment, dynamic symmetry calculation for any subsets, 2D cartoons at different levels, and interactive contact maps. iCn3D can also be used in Jupyter Notebook as described at https://pypi.org/project/icn3dpy.

scholarly journals Changes in protein structure at the interface accompanying complex formation

IUCrJ ◽  
2015 ◽  
Vol 2 (6) ◽  
pp. 643-652 ◽  
Author(s):  
Devlina Chakravarty ◽  
Joël Janin ◽  
Charles H. Robert ◽  
Pinak Chakrabarti
Keyword(s):  
Secondary Structure ◽  
Complex Formation ◽  
Protein Interactions ◽  
Protein Structures ◽  
Accessible Surface Area ◽  
Solvent Accessible Surface Area ◽  
Successful Implementation ◽  
Data Set ◽  
Protein Protein Interaction ◽  
Interface Residues

Protein interactions are essential in all biological processes. The changes brought about in the structure when a free component forms a complex with another molecule need to be characterized for a proper understanding of molecular recognition as well as for the successful implementation of docking algorithms. Here, unbound (U) and bound (B) forms of protein structures from the Protein–Protein Interaction Affinity Database are compared in order to enumerate the changes that occur at the interface atoms/residues in terms of the solvent-accessible surface area (ASA), secondary structure, temperature factors (Bfactors) and disorder-to-order transitions. It is found that the interface atoms optimize contacts with the atoms in the partner protein, which leads to an increase in their ASA in the bound interface in the majority (69%) of the proteins when compared with the unbound interface, and this is independent of the root-mean-square deviation between the U and B forms. Changes in secondary structure during the transition indicate a likely extension of helices and strands at the expense of turns and coils. A reduction in flexibility during complex formation is reflected in the decrease inBfactors of the interface residues on going from the U form to the B form. There is, however, no distinction in flexibility between the interface and the surface in the monomeric structure, thereby highlighting the potential problem of usingBfactors for the prediction of binding sites in the unbound form for docking another protein. 16% of the proteins have missing (disordered) residues in the U form which are observed (ordered) in the B form, mostly with an irregular conformation; the data set also shows differences in the composition of interface and non-interface residues in the disordered polypeptide segments as well as differences in their surface burial.

scholarly journals PPI layouts: BioJS components for the display of Protein-Protein Interactions

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 50 ◽  
Author(s):  
Gustavo A. Salazar ◽  
Ayton Meintjes ◽  
Nicola Mulder
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Third Party ◽  
Protein Protein Interactions ◽  
Web Based ◽  
Protein Protein Interaction ◽  
Link Type ◽  
Protein Protein Interaction Networks

Summary: We present two web-based components for the display of Protein-Protein Interaction networks using different self-organizing layout methods: force-directed and circular. These components conform to the BioJS standard and can be rendered in an HTML5-compliant browser without the need for third-party plugins. We provide examples of interaction networks and how the components can be used to visualize them, and refer to a more complex tool that uses these components. Availability: http://github.com/biojs/biojs; http://dx.doi.org/10.5281/zenodo.7753

User password repetitive patterns analysis and visualization

2016 ◽  
Vol 24 (1) ◽  
pp. 93-115 ◽  
Author(s):  
Xiaoying Yu ◽  
Qi Liao
Keyword(s):  
Security Policy ◽  
Large Data ◽  
Efficient Algorithms ◽  
Privacy And Security ◽  
Data Set ◽  
Web Based ◽  
Content Type ◽  
Word Cloud ◽  
Individual Privacy ◽  
Password Security

Purpose – Passwords have been designed to protect individual privacy and security and widely used in almost every area of our life. The strength of passwords is therefore critical to the security of our systems. However, due to the explosion of user accounts and increasing complexity of password rules, users are struggling to find ways to make up sufficiently secure yet easy-to-remember passwords. This paper aims to investigate whether there are repetitive patterns when users choose passwords and how such behaviors may affect us to rethink password security policy. Design/methodology/approach – The authors develop a model to formalize the password repetitive problem and design efficient algorithms to analyze the repeat patterns. To help security practitioners to analyze patterns, the authors design and implement a lightweight, Web-based visualization tool for interactive exploration of password data. Findings – Through case studies on a real-world leaked password data set, the authors demonstrate how the tool can be used to identify various interesting patterns, e.g. shorter substrings of the same type used to make up longer strings, which are then repeated to make up the final passwords, suggesting that the length requirement of password policy does not necessarily increase security. Originality/value – The contributions of this study are two-fold. First, the authors formalize the problem of password repetitive patterns by considering both short and long substrings and in both directions, which have not yet been considered in past. Efficient algorithms are developed and implemented that can analyze various repeat patterns quickly even in large data set. Second, the authors design and implement four novel visualization views that are particularly useful for exploration of password repeat patterns, i.e. the character frequency charts view, the short repeat heatmap view, the long repeat parallel coordinates view and the repeat word cloud view.

A batch-wise non-linear fitting and analysis tool for treating large X-ray diffraction data sets

2006 ◽  
Vol 39 (2) ◽  
pp. 262-266 ◽  
Author(s):  
R. J. Davies
Keyword(s):  
Diffraction Data ◽  
Operation Mode ◽  
Large Data ◽  
Scattering Data ◽  
Data Sets ◽  
Analysis Tool ◽  
Data Set ◽  
X Ray ◽  
Linear Fitting ◽  
Non Linear

Synchrotron sources offer high-brilliance X-ray beams which are ideal for spatially and time-resolved studies. Large amounts of wide- and small-angle X-ray scattering data can now be generated rapidly, for example, during routine scanning experiments. Consequently, the analysis of the large data sets produced has become a complex and pressing issue. Even relatively simple analyses become difficult when a single data set can contain many thousands of individual diffraction patterns. This article reports on a new software application for the automated analysis of scattering intensity profiles. It is capable of batch-processing thousands of individual data files without user intervention. Diffraction data can be fitted using a combination of background functions and non-linear peak functions. To compliment the batch-wise operation mode, the software includes several specialist algorithms to ensure that the results obtained are reliable. These include peak-tracking, artefact removal, function elimination and spread-estimate fitting. Furthermore, as well as non-linear fitting, the software can calculate integrated intensities and selected orientation parameters.

scholarly journals SNOW, a web-based tool for the statistical analysis of protein–protein interaction networks

2009 ◽  
Vol 37 (suppl_2) ◽  
pp. W109-W114 ◽  
Author(s):  
Pablo Minguez ◽  
Stefan Götz ◽  
David Montaner ◽  
Fatima Al-Shahrour ◽  
Joaquin Dopazo
Keyword(s):  
Statistical Analysis ◽  
Protein Interaction ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Web Based ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Networks

scholarly journals Protein-protein-interaction Network Organization of the Hypusine Modification System

2012 ◽  
Vol 11 (11) ◽  
pp. 1289-1305 ◽  
Author(s):  
Henning Sievert ◽  
Simone Venz ◽  
Oscar Platas-Barradas ◽  
Vishnu M. Dhople ◽  
Martin Schaletzky ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Large Scale ◽  
Affinity Purification ◽  
Interaction Network ◽  
Initiation Factor ◽  
Post Translational Modification ◽  
Comprehensive Overview ◽  
Data Set ◽  
Modification System ◽  
Protein Protein Interaction

Hypusine modification of eukaryotic initiation factor 5A (eIF-5A) represents a unique and highly specific post-translational modification with regulatory functions in cancer, diabetes, and infectious diseases. However, the specific cellular pathways that are influenced by the hypusine modification remain largely unknown. To globally characterize eIF-5A and hypusine-dependent pathways, we used an approach that combines large-scale bioreactor cell culture with tandem affinity purification and mass spectrometry: “bioreactor-TAP-MS/MS.” By applying this approach systematically to all four components of the hypusine modification system (eIF-5A1, eIF-5A2, DHS, and DOHH), we identified 248 interacting proteins as components of the cellular hypusine network, with diverse functions including regulation of translation, mRNA processing, DNA replication, and cell cycle regulation. Network analysis of this data set enabled us to provide a comprehensive overview of the protein-protein interaction landscape of the hypusine modification system. In addition, we validated the interaction of eIF-5A with some of the newly identified associated proteins in more detail. Our analysis has revealed numerous novel interactions, and thus provides a valuable resource for understanding how this crucial homeostatic signaling pathway affects different cellular functions.

scholarly journals PINAWeb: A web-based tool for the comparison of Protein-Protein Interaction Networks Aligners

2021 ◽  
Author(s):  
A. Alcalá ◽  
G. Riera ◽  
I. García ◽  
R. Alberich ◽  
M. Llabrés
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Protein Protein Interactions ◽  
Considerable Effort ◽  
Web Based ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Networks ◽  
User Friendly

AbstractMotivationSeveral protein-protein interaction networks (PPIN) aligners have been developed during the last 15 years. One of their goals is to help the functional annotation of proteins and the prediction of protein-protein interactions. A correct aligner must preserve the network’s topology as well as the biological coherence. However, this is a trade-off that is hard to achieve. In addition, most aligners require a considerable effort to use in practice and many researchers must choose an aligner without the opportunity to previously compare the performance of different aligners.ResultsWe developed PINAWeb, a user-friendly web-based tool to obtain and compare the results produced by the aligners: AligNet, HubAlign, L-GRAAL, PINALOG and SPINAL. PPINs can be uploaded either from the STRING database or from a user database. The source code of PINAWeb is freely available on GitHub to enable researchers to add other aligners, network databases or alignment score metrics. In addition, PINAWeb provides a report with the analysis for every alignment in terms of topological and functional information scores, as well as the visualization of the alignments’ comparison (agreement/differences) when more than one aligner are considered.Availabilityhttps://bioinfo.uib.es/~recerca/PINAWeb

scholarly journals Biological Network Analysis of Genes Involve in Embryogenesis of Oil Palm using ClueGO

2017 ◽  
Vol 3 (4) ◽  
pp. 265
Author(s):  
Widyartini Made Sudania ◽  
Zulfikar Achmad Tanjung ◽  
Nurita Toruan-Mathius ◽  
Tony Liwang
Keyword(s):  
Dna Sequencing ◽  
Oil Palm ◽  
Biological Networks ◽  
Expressed Sequence Tag ◽  
Large Data ◽  
Data Interpretation ◽  
Analysis Tool ◽  
Sequencing Data ◽  
Data Set ◽  
Kegg Pathways

<p class="Els-Abstract-text">The application of DNA sequencing technologies has a major impact on molecular biology, especially in understanding genes interaction in a certain condition. Due to a large number of genes produced by this high-throughput technology, a proper analysis tool is needed for data interpretation. ClueGO is a bioinformatics tool, an easy to use Cytoscape plug-in that strongly improves biological function interpretation of genes. It analyzes a cluster or comparing two clusters and comprehensively visualizes their group functions. This tool is applied to identify biological networks of genes involved in embryogenesis of oil palm, the most critical phase in oil palm tissue culture process. Two ESTs sequencing data from the GenBank database under accession number EY396120-EY413718 and DW247764-DW248770 were used in this study. Fifty-two and one hundred eight groups of genes were identified using biological process in Gene Ontology setting from the database of EY396120-EY413718 and DW247764-DW248770, respectively. Thirty-one groups of genes were consistently occurred in both ESTs. According to the literature, these genes play an important role in cell formations and developments, stresses and stimulus responses, photosynthesis and metabolic processes that indicate the involvement of these groups of genes in oil palm embryogenesis processes. ClueGO is the appropriate tool to analyze a large data set of genes in a specific condition, such as embryogenesis of oil palm.</p><div><p class="Els-keywords"><em> </em></p></div><strong>Keywords:</strong> callus embryogenesis; Cytoscape plug-in; DNA sequencing; expressed sequence tag; KEGG pathways

scholarly journals DELPHI: accurate deep ensemble model for protein interaction sites prediction

2020 ◽  
Author(s):  
Yiwei Li ◽  
Lucian Ilie
Keyword(s):  
Deep Learning ◽  
Protein Interaction ◽  
Binding Sites ◽  
Data Augmentation ◽  
Fundamental Problem ◽  
Art Programs ◽  
Protein Protein Interaction ◽  
Interaction Sites ◽  
Link Type ◽  
Protein Interaction Sites

AbstractMotivationProteins usually perform their functions by interacting with other proteins, which is why accurately predicting protein-protein interaction (PPI) binding sites is a fundamental problem. Experimental methods are slow and expensive. Therefore, great efforts are being made towards increasing the performance of computational methods.ResultsWe propose DELPHI (DEep Learning Prediction of Highly probable protein Interaction sites), a new sequence-based deep learning suite for PPI binding sites prediction. DELPHI has an ensemble structure with data augmentation and it employs novel features in addition to existing ones. We comprehensively compare DELPHI to nine state-of-the-art programs on five datasets and show that it is more accurate.AvailabilityThe trained model, source code for training, predicting, and data processing are freely available at https://github.com/lucian-ilie/DELPHI. All datasets used in this study can be downloaded at http://www.csd.uwo.ca/~ilie/DELPHI/[email protected]

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