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Analysis Of Human Genome To Predict The Development Of Illnesses

The GARBAN project, drawn up by Navarre University, will enable the identification of therapeutic targets for cancer, depression and hepatitis.

The School of Engineering at Navarre University and its Centre for Technical Studies and Research in Gipuzkoa (CEIT) have launched an advanced biochemical analysis tool that will help in predicting the evolution of diseases, accelerate their diagnosis and identify new therapeutic targets (lines of action) for ailments such as cancer, depression and hepatitis.

This bioinformatics tool, designed in collaboration with the Centre for Applied Research in Medicine (CIMA) at Navarre University and known as GARBAN (Genomic Analysis for Rapid Biological Annotation), carries out the following process: firstly, it hierarchically classifies all known genes and proteins according to their molecular function, molecular composition and biological process. With the unknown ones, they are logged (comparing similarities and differences with respect to these same molecules in other living things) and molecules with a similar sequence
to theirs are observed in order to deduce their function and to classify them in the same order as the molecules already known.

The project also includes all genes and proteins ordered according to their behaviour in determined circumstances. To this end, it compares the same genes and proteins amongst healthy and unwell persons and amongst ill persons receiving different treatment. In this way, the behaviour of these molecules at different moments in the illness is registered.

Available on Internet

Once the function and behaviour of the genes and proteins are registered, this analysis tool detects anomalous behaviour of these molecules that could give rise to an illness and presents all this graphically as a map and thus, the doctor can anticipate the development of the illness. If the ailment has already initiated, this system enables a visual graphical representation of the overall cellular cycles involved in the illness and
provides information on the evolution of the sickness using the gathered data. Using the appropriate analyses, it enables the measurement of the efficiency of and patient response to the different treatments administered, thus enabling the identification of new, more effective therapeutic targets.

This new tool is available on Internet, thus enabling any biochemist working in genomics o proteonics to access the information generated in similar studies and research the similarities and comparisons which can throw light on some of the obscure aspects of many diseases.


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Source:Navarre University


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