A systematic review of network analyst – Pubrica

1. A SYSTEMATIC REVIEW OF NETWORK ANALYST- A WEB BASED BIOINFORMATICS TOOL FOR INTEGRATIVE VISUALIZATION OF EXPRESSIONDATA An Academic presentationby Dr.NancyAgens,Head,TechnicalOperations,Pubrica Group: www.pubrica.com Email:sales@pubrica.com

2. Today'sDiscussion Outline In-Brief Introduction Steps Involved in PPIAnalysis Key Features of the Network Analyst Program Description and Methods Implementation Limitations Conclusion

3. In-Brief In aSystematic Review Writing, the network analyst is a bioinformatics tool designed to perform efficient PPI network analysis for data generated fromgene expression experiments the following contents explain about the network analyst and their methods, in brief, using the help of pubrica blog. SystematicReview writingServicesfor network analysis purposes explain you about theintegrative visualization of data expression used in health caresectors

4. Introduction Network analyst is a web based visual analytics tool for comprehensive profiling, Meta analysis andsystem-level interpretation of gene expression data which is based on PPI network analysis andvisualization. The first version of Network analyst was launched in 2014; there are various updates attached afterwards based onthe community feedback and technologyprogress. In the latest version users able to perform gene expression for 17 different species and other benefits such ascreating cell or tissue-specific PPI networks, gene regulatory networks, gene co-expression networks using systematic reviewservices

5. Steps Involved in PPIAnalysis After conductinga systematic review, there arethree significant steps involved in PPIanalysis To identify the gene or protein of interestwhich includes differentially expressed genes, the genewith nucleotide polymorphism and gene-targetedby microRNAs The input data is to search and find binaryinformation from a systemized PPIdatabase There are two complementary approaches performedin the third step, Topology analysis and Moduleanalysis

6. KeyFeatures of the Network Analyst Supports gene or protein list and single or multiplegene expression data. Flexible differential expression and analysis formultiple experimentaldesigns. Multiple options provide the control of networksize. Interactive network visualization with otherfeatures such as facile searching, zooming and highlighting by writing a systematicreview. Contd..

7. Supports topology, module and shortest-pathanalysis Functional enrichment analysis on current selection includes GO, KEGG,Reactome Customize options with layout, edge shapes and node size, colour,visibility Network features including node deletion and moduleextraction The output downloads the network files (edge list, graphML), Images (PNG,PDF) and Topology or Functional analysisresult

8. Program Description and Methods There are three significant steps in working of network analyst based onSystematic Reviewwriting Data processing to identify thegenes Network construction for mapping, buildingand refiningnetworks Network analysisandvisualization

9. 1. Data Processing Data processinginvolves Data formats anduploading Data processing andannotation Data normalization andanalysis

10. 2. Network Construction Network analystwill give a detailed, high-quality PPI database obtained from InnateDB in the InternationalMolecular Exchange(IME)Consortium. The experimental PPI database is from IntAct, MINT, DIP, BING, andBioGRID. The database consists of 14,775 proteins, 1, 45,995 experimentally confirmed interaction for humans and 5657 proteins, 14,491 interactions formouse. Contd..

11. For every individual protein, a search algorithm is created, which is capable of direct interaction with seedprotein. The results utilize to build the default networks. The users advise controlling the number of nodes within 200 to 2000 for practical reasons because larger systems lead to Hairballeffect

12. 3.Hairball Effect When the network becomes large and complex, it suffers from the hairball effect, which significantly affects thepractical utilities and uptake. Two steps follow to resolve thisissue Trimming the default network to retain onlythose significant nodes oredges Developing better visualization methods to reduceedge and nodeocclusion Contd..

14. 4.Network Analysis There are five significantpanels Network explorer- shows all networks created fromseed proteins Hub explorer– consist of detailed information of nodeswithin the currentnetwork Module explorer-permits the user to decompose thecurrent network into condensedmodules Functional explorer– permits the user to detecttheshortest path between twonodes

15. 5. Network Visualization There are certain events recommended to follow for visualization and these events are carried using the mouse, there are various user-friendly options are available suchas Node displayoption Networkoption Node deletion and moduleextraction

16. Implementation The construction of Network analyst interface using java server faces 2.0 technology reliesbased on visualization issigma. Js Java script library, backend statistical computation was implemented using Rprogram language, construction of the layoutalgorithm based on Gephi tool kit, PPI database are storedin Neo4j graphdatabase. The network analysttakes a test withmajor modern browsers with HTML support such as Google Chrome, Mozilla Firefox andMicrosoft InternetExplorer

17. Limitations PPI database may contain falsepositives Unable to determine new interactions whichare condition-specific The plansinclude Increase its support for moreorganisms More updates in the Visualizationfield

18. Conclusion Biological network analysis is difficult to getinsight into complex diseases or biological systems, network analyst easy to use web based tool assistbench researchers and clinicians to perform various tasks and highly userfriendly. Pubrica helps you to know about the workflow of network analyst in a detailed manner withwritinga systematic literature reviewfor futurepurposes.

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