Non-additivity in protein-DNA binding.

@article{citeulike:833519, abstract = {MOTIVATION: Localizing protein binding sites within genomic DNA is of considerable importance, but remains difficult for protein families, such as transcription factors, which have loosely defined target sequences. It is generally assumed that protein affinity for DNA involves additive contributions from successive nucleotide pairs within the target sequence. This is not necessarily true, and non-additive effects have already been experimentally demonstrated in a small number of cases. The principal origin of non-additivity involves the so-called indirect component of protein-DNA recognition which is related to the sequence dependence of DNA deformation induced during complex formation. Non-additive effects are difficult to study because they require the identification of many more binding sequences than are normally necessary for describing additive specificity (typically via the construction of weight matrices). RESULTS: In the present work we will use theoretically estimated binding energies as a basis for overcoming this problem. Our approach enables us to study the full combinatorial set of sequences for a variety of DNA-binding proteins, make a detailed analysis of non-additive effects and exploit this information to improve binding site predictions using either weight matrices or support vector machines. The results underline the fact that, even in the presence of significant deformation, non-additive effects may involve only a limited number of dinucleotide steps. This information helps to reduce the number of binding sites which need to be identified for successful predictions and to avoid problems of over-fitting. AVAILABILITY: The SVM software is available upon request from the authors.}, address = {Department of Physics and Astronomy, BioMaps Institute, Rutgers, The State University of New Jersey, 136 Frelinghuysen Road, Piscataway, NJ 08854-8019, USA.}, author = {O'Flanagan, R. A. and Paillard, G. and Lavery, R. and Sengupta, A. M. }, citeulike-article-id = {833519}, issn = {1367-4803}, journal = {Bioinformatics}, keywords = {binding-site-prediction, bioinformatics, svm}, month = {May}, number = {10}, pages = {2254--2263}, posted-at = {2008-01-24 20:09:14}, priority = {3}, title = {Non-additivity in protein-DNA binding.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/15746285}, volume = {21}, year = {2005} }

TY - JOUR ID - citeulike:833519 L3 - citeulike-article-id:833519 TI - Non-additivity in protein-DNA binding. JF - Bioinformatics VL - 21 IS - 10 SP - 2254 EP - 2263 AD - Department of Physics and Astronomy, BioMaps Institute, Rutgers, The State University of New Jersey, 136 Frelinghuysen Road, Piscataway, NJ 08854-8019, USA. SN - 1367-4803 N2 - MOTIVATION: Localizing protein binding sites within genomic DNA is of considerable importance, but remains difficult for protein families, such as transcription factors, which have loosely defined target sequences. It is generally assumed that protein affinity for DNA involves additive contributions from successive nucleotide pairs within the target sequence. This is not necessarily true, and non-additive effects have already been experimentally demonstrated in a small number of cases. The principal origin of non-additivity involves the so-called indirect component of protein-DNA recognition which is related to the sequence dependence of DNA deformation induced during complex formation. Non-additive effects are difficult to study because they require the identification of many more binding sequences than are normally necessary for describing additive specificity (typically via the construction of weight matrices). RESULTS: In the present work we will use theoretically estimated binding energies as a basis for overcoming this problem. Our approach enables us to study the full combinatorial set of sequences for a variety of DNA-binding proteins, make a detailed analysis of non-additive effects and exploit this information to improve binding site predictions using either weight matrices or support vector machines. The results underline the fact that, even in the presence of significant deformation, non-additive effects may involve only a limited number of dinucleotide steps. This information helps to reduce the number of binding sites which need to be identified for successful predictions and to avoid problems of over-fitting. AVAILABILITY: The SVM software is available upon request from the authors. KW - binding-site-prediction KW - bioinformatics KW - svm AU - O'Flanagan, RA AU - Paillard, G AU - Lavery, R AU - Sengupta, AM PY - 2005/05/15/ UR - http://view.ncbi.nlm.nih.gov/pubmed/15746285 ER -