New bioinformatics software company launched

FactBio will develop new products for knowledge management and improved data discovery

FactBio, a developer of bioinformatics software with a focus on improving knowledge management and data sharing, has been established.

The company will develop new bioinformatics software to improve life sciences research, focusing on the development of Kusp (Knowledge Sharing Platform), a knowledge management system which will allow researchers to select a series of BioBuckets and use these to track entities of interest to them, and receive updates of new developments.

The entities could include genes, pathways, proteins, or even people and publications as required. Kusp will also be fully integrated into social media, allowing researchers to share their discoveries with the global community.

Users of Kusp will be able to employ a number of BioBuckets to track entities of interest free of charge, but users who want to keep abreast of a wider range will have to pay a fee. Packages will also be available for enterprise users.

Alongside Kusp, which will be launched early next year, FactBio plans to develop additional bioinformatics software products.

In addition, the company is working with a number of life science companies on a consultancy basis and is running a series of training events for bioinformaticians.

Dr James Malone, CEO of FactBio, said: 'With the increasing amount of data now available to researchers, there is a need for new and improved ways to monitor an increasing range of interests. Through Kusp, researchers can automate keeping track of their many interests. In addition, FactBio will also be developing advanced analysis software, drawing on our machine learning background.'

The company has been established by Malone, who is CEO, with Tony Stephenson as Chief Operating Officer, alongside Simon Jupp as Technology Consultant.

Malone and Jupp have particular experience in projects such as Centre for Therapeutic Target Validation, EBI Linked Data Platform, Orphanet Rare Disease, and Experimental Factor Ontology.

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