A new way to search PubMed

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So much more than static images of pathways.

Vizit is a visual bibliographic search tool. Which means that unlike PubMed or Google, when users type in a search term, instead of a list of publications, they get a visual network of related terms.

So you can start with a gene and ask Vizit to show pathways or diseases related to it. Or you can look up a disease and instruct Vizit to show cell lines used to study it.

Vizit with antibodies

In an unbiased graph of biological connections straight from PubMed.

Vizit with notes

Vizit users can explore these relationships by expanding the network any which way they want. And when they need to learn more they can bring up all the related scientific publications.

They can save their search results and create notes with additional findings, their opinions or questions. And they can share these networks and notes with a simple url that will direct their peers automatically to your site.

A rich set of search categories.

With Vizit all genes, pathways, cell lines, PTMs and diseases are covered. There's more than 30 categories to pick from.

Vizit with notes

Genes from human/mouse/rat plus >200 other model organisms. Includes genes from the Human Microbiome Project.

Over 60 Post-translational modifications (phosphorylation, glycosylation and more).

Pathways, Complexes and Biosystems from NCBI Biosystems, Gene Ontology, KEGG, Reactome and more

All cell lines from leading catalogues, including ATCC, CLDB and others.

All Diseases and Medical conditions covered in UMLS.

Laboratory, diagnostic and medical tests and procedures.

Great sharing capabilities.

Helping you collaborate faster and more efficiently.

With Vizit, scientists with similar research interests can self organize into virtual communities. They can share information and opinions - like some common research challenge.

Vizit social cloud

Users can save the networks they create. And they can share their insights with their peers.

Twitter, Linkedin, Facebook, Email. They’re all covered.

Proven in the field.

Biovista is a pioneer in the field of literature mining technologies. Our tools have been used with pharma companies, payor organizations and regulators around the world to predict new indications for existing drugs and identify non-obvious adverse drug reactions.

View relevant publications from Biovista

1: Gronich N, Deftereos SN, Lavi I, Persidis AS, Abernethy DR, Rennert G. Hypothyroidism Is a Risk Factor for New-Onset Diabetes: A Cohort Study. Diabetes Care. 2015 Sep;38(9):1657-64. PubMed PMID: 26070591.

2: Andronis C, Sharma A, Virvilis V, Deftereos S, Persidis A. Literature mining, ontologies and information visualization for drug repurposing. Brief Bioinform. 2011 Jul;12(4):357-68. Review. PubMed PMID: 21712342.

3: Deftereos SN, Andronis C, Friedla EJ, Persidis A, Persidis A. Drug repurposing and adverse event prediction using high-throughput literature analysis. Wiley Interdiscip Rev Syst Biol Med. 2011 May-Jun;3(3):323-34. Review. PubMed PMID: 21416632.

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