Kajeka supply analysis solutions to biosciences and beyond. Our ground-breaking software allow you to reveal hidden relationships in complex data.

With over ten years of development history, the technology that underpins our stunningly visual analytical approach to data analysis will enable you to see clarity from complexity allowing you to make the right decisions faster than ever before.

Ground-breaking analysis tools

Great uses of Kajeka’s software

Kajeka’s data analysis approach and supporting software is designed to handle a wide variety of data types and be applicable across a wide range of industries. Below are just of the few examples of where and how it can be used.

1. An atlas of human gene activity

In a recent study led by the Riken Institute, Japan and published in the journal Nature, an international team of scientists explored large volumes of data defining not only which genes were expressed across a large range of human cells and tissues, but the exact start sites of transcription (promoters). After a preliminary analysis the team defined over 184,000 such sites across the human genome. Using the technology behind Kajeka to explore these data, they were able to define function relationships between genes based on their coexpression across the samples.


2. Redefining acute mountain sickness

The syndrome of acute mountain sickness has existed unchanged, by international consensus, for decades. Clinical experience at high altitude, combined with emerging understanding of the pathophysiology of the condition, prompted a new investigation into whether different individuals might exhibit different patterns of disease. Visualising the data collected using our approach revealed a clear pattern: most patients experience sleep disturbance without headache, a small subgroup experience headache without sleep disturbance. Other symptoms are either ubiquitous or rare. This novel observation allowed researchers to conclude that acute mountain sickness comprises at least two distinct clinical syndromes. These findings have directly led to a re-definition of acute mountain sickness and a new consensus definition will be released in 2015.

3. Analysis of share price data

The share price of a company may fluctuate and understanding and predicting these changes in the context of the market as a whole is a major challenge. Using our approach to data science it is possible to explore the share price behaviour of all companies at once and to understand relationships between companies based on their relationships to each other. If you understand the behaviour of the market as a whole based on past performance, you can better predict the future.

NASDAQ Stock Data: 2008 – 2009

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