![]() ![]() DNA-binding proteins comprise DNA-binding domains such as the helix-turn-helix (HTH), the zinc finger and the leucine zipper, among others ( 5). DNA-binding proteins play a vital role in the delivery of this information DNA-binding proteins ( 3) include transcription factors that modulate the transcription process, nucleases that cleave DNA molecules and histones that are involved in DNA packaging in the cell nucleus ( 4). The mechanisms for encoding, decoding and transmitting genetic information have been the focus of much attention. Since the discovery of the DNA double helix in 1953 and the ‘central dogma’ of molecular biology ( 1), which has been questioned and subsequently revised, research and debate on the flow of genetic information have been continuous ( 2). #HELIX SERVER FIU SOFTWARE#Software for mining LCVs from sequence data set can be obtained from anonymous ftp site. Furthermore, genome-wide predictions detect new HTH proteins in both Homo sapiens and Escherichia coli organisms, which enlarge applications of the LCV approach. The LCV approach is to some extent a complementary to the profile-HMM models for its better identification of false-positive data. Comparisons with profile-HMM models from the Pfam protein families database show that the LCV approach maintains a good balance while dealing with HTH-containing proteins and non-HTH proteins at the same time. Prediction results of newly reported HTH-containing proteins compared with other prediction web service presents a good prediction model derived from the LCV approach. ![]() Our approach predicts HTH motifs more precisely using only primary protein sequence information, with 93.29% accuracy, 93.93% sensitivity and 92.66% specificity. The large data set we used comprises 13 HTH families, with 17 455 sequences in total. Prediction ability of LCV sets at different thresholds is calculated to settle a moderate threshold. Then after LCS refinement, local combinational variables (LCV) are generated to construct prediction models for HTH motifs. First we choose a sequence data set for 88 proteins of 22 amino acids in length to launch an optimized traversal for extracting local combinational segments (LCS) from the data set. In this work, we develop a local combinational variable approach for sequence-based helix-turn-helix (HTH) motif prediction. Sequence-based approach for motif prediction is of great interest and remains a challenge. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |