In recent years, microRNAs (miRNAs), a class of 19-25 nucleotides noncoding RNAs, have been shown to play a major role in gene regulation across a broad range of metazoans and are important for a diverse biological functions. These miRNAs are involved in the regulation of protein expression primarily by binding to one or more target sites on an mRNA transcript and causing cleavage or repression of translation. Computer-based approaches for miRNA gene identification and miRNA target prediction are being considered as indispensable in miRNA research. Similarly, effective experimental techniques validating in silico predictions are crucial to the testing and finetuning of computational algorithms. Iterative interactions between in silico and experimental methods are now playing a central role in the biology of miRNAs. In this review, we summarize the various computational methods for identification of miRNAs and their targets as well as the technologies that have been developed to validate the predictions.