Computational methods for theidentification of differential and coordinated gene expression.
Jean-Michel Claverie
Human Molecular Genetics, 1999, 8(10):1821-1832
With the first complete ‘draft’ of the human genome sequence expected for Spring 2000, the three basic challenges for today’s bioinformatics are more than ever:(i) finding the genes; (ii) locating their coding regions; and (iii) predicting their functions. However, our capacity for interpreting vertebrate genomic and transcript (cDNA) sequences using experimental or computational means very much lags behind our raw sequencing power. If the performances of current programs in identifying internal coding exons are good, the precise 5\'->3\' delineation of transcription units (and promoters) still requires additional experiments. Similarly, functional predictions made with reference to previously characterized homologues are leaving >50% of human genes unannotated or classified in uninformative categories(‘kinase’, ‘ATP-binding’, etc.).In the context of functional genomics, large-scale gene expression studies using massive cDNA tag sequencing, two-dimensional gel proteome analysis or microarray technologies are the only approaches providing genome-scale experimental information at a pace consistent withthe progress of sequencing. Given the difficulty and cost of characterizing genes one by one, academic and industrial researchers are increasinglyrelying on those methods to prioritize their studies and choosetheir targets. The study of expression patterns can also providesome insight into the function, reveal regulatory pathways, indicateside effects of drugs or serve as a diagnostic tool. In this article,I review the theoretical and computational approaches used to: (i)identify genes differentially expressed (across cell types, developmental stages, pathological conditions, etc.); (ii) identify genes expressedin a coordinated manner across a set of conditions; and (iii) delineateclusters of genes sharing coherent expression features, eventually defining global biological pathways.
(med UI: id:89) .