Vipin Narang (email@example.com)
Wing-Kin Sung (firstname.lastname@example.org)
Ankush Mittal (email@example.com)
Department of Computer Science, 3 Science Drive 2, National University of Singapore, 117543, Singapore
Department of Electronics and Computer Engineering, Indian Institute of Technology, Roorkee-247667, Uttaranchal, India
Drosophila melanogaster is one of the most important organisms for studying the genetics of development. The precise regulation of genes during early development is enacted through the control of transcription. The control circuitry is hardwired in the genome as clusters of multiple transcription factor binding sites (TFBS) known as cis-regulatory modules (CRMs). A number of TFBS and CRMs have been experimentally annotated in the Drosophila genome. Currently about 661 CRM sequences are known, of which 155 have been annotated with 778 TFBS. This work attempts computational annotation of TFBS in the remaining 506 uncharacterized Drosophila CRMs. The difficulty of this task lies in the fact that experimental data is insufficient for constructing reliable positional weight matrices (PWM) to predict the TFBS. Thus a novel feature extraction and classification method for TFBS detection has been implemented in this work. The method achieves both high sensitivity and low false positive rate in cross-validation studies. As a result of this work, a new database has been compiled which aggregates all the CRM and TFBS annotation information for Drosophila available to date, and appends new TFBS annotations.