Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Background#R##N#The huge amount of data generated by DNA chips is a porful basis to classify various pathologies. Hover, constant evolution of microarray technology makes it difficult to mix data from different chip types for class prediction of limited sample populations. Affymetrix® technology provides both a quantitative fluorescence signal and a decision (detection call: absent or present) based on signed-rank algorithms applied to several hybridization repeats of each gene, with a per-chip normalization.  developed a new prediction method for class belonging based on the detection call only from recent Affymetrix chip type. Biological data re obtained by hybridization on U133A, U133B and U133Plus 2.0 microarrays of purified normal B cells and cells from three independent groups of multiple myeloma (MM) patients.
['Thierry Rème', 'Dirk Hose', 'John De Vos', 'Aurélien Vassal', 'Pierre-Olivier Poulain', 'Véronique Pantesco', 'Hartmut Goldschmidt', 'Bernard Klein']
I am writing a research paper on a idea A new method for class prediction based on signed-rank algorithms applied to Affymetrix ® microarray experiments
[{"from": "human", "value": "I am writing a research paper on a idea A new method for class prediction based on signed-rank algorithms applied to Affymetrix \u00ae microarray experiments"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Background#R##N#The huge amount of data generated by DNA chips is a porful basis to classify various pathologies. Hover, constant evolution of microarray technology makes it difficult to mix data from different chip types for class prediction of limited sample populations. Affymetrix\u00ae technology provides both a quantitative fluorescence signal and a decision (detection call: absent or present) based on signed-rank algorithms applied to several hybridization repeats of each gene, with a per-chip normalization.  developed a new prediction method for class belonging based on the detection call only from recent Affymetrix chip type. Biological data re obtained by hybridization on U133A, U133B and U133Plus 2.0 microarrays of purified normal B cells and cells from three independent groups of multiple myeloma (MM) patients."}]