Information content of individual genetic sequences. Export

@article{citeulike:439298, abstract = {Related genetic sequences having a common function can be described by Shannon's information measure and depicted graphically by a sequence logo. Though useful for many purposes, sequence logos only show the average sequence conservation, and inferring the conservation for individual sequences is difficult. This limitation is overcome by the individual information ( R i) technique described here. The method begins by generating a weight matrix from the frequencies of each nucleotide or amino acid at each position of the aligned sequences. This matrix is then applied to the sequences themselves to determine the sequence conservation of each individual sequence. The matrix is unique because the average of these assignments is the total sequence conservation, ad there is only one way to construct such a matrix. For binding sites on polynucleotides, the weight matrix has a natural cut off that distinguishes functional sequences from other sequences. R i values are on an absolute scale measured in bits of information so the conservation of different biological functions can be compared with one another. The matrix can be used to rank-order the sequences, to search for new sequences, to compare sequences to other quantitative data such as binding energy or distance between binding sites, to distinguish mutations from polymorphisms, to design sequences of a given strength, and to detect errors in databases. The R i method has been used to identify previously undescribed but experimentally verified DNA binding sites. The individual information distribution was determined for E. coli ribosome binding sites, bacterial Fis binding sites, and human donor and acceptor splice junctions, among others. The distributions demonstrate clearly that the consensus sequence is highly unusual, and hence is a poor method to describe naturally occurring binding sites.}, address = {National Cancer Institute, Frederick Cancer Research and Development Center, Laboratory of Mathematical Biology, P.O. Box B, Frederick, MD 21702-1201, USA. toms@ncifcrf.gov}, author = {Schneider, T. D.}, citeulike-article-id = {439298}, citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/9446751}, citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=9446751}, day = {21}, issn = {0022-5193}, journal = {J Theor Biol}, keywords = {informationtheory, sequencealignment, statistics}, month = {December}, number = {4}, pages = {427--441}, posted-at = {2005-12-16 03:44:49}, priority = {2}, title = {Information content of individual genetic sequences.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/9446751}, volume = {189}, year = {1997} }

TY - JOUR ID - citeulike:439298 L3 - citeulike-article-id:439298 N2 - Related genetic sequences having a common function can be described by Shannon's information measure and depicted graphically by a sequence logo. Though useful for many purposes, sequence logos only show the average sequence conservation, and inferring the conservation for individual sequences is difficult. This limitation is overcome by the individual information ( R i) technique described here. The method begins by generating a weight matrix from the frequencies of each nucleotide or amino acid at each position of the aligned sequences. This matrix is then applied to the sequences themselves to determine the sequence conservation of each individual sequence. The matrix is unique because the average of these assignments is the total sequence conservation, ad there is only one way to construct such a matrix. For binding sites on polynucleotides, the weight matrix has a natural cut off that distinguishes functional sequences from other sequences. R i values are on an absolute scale measured in bits of information so the conservation of different biological functions can be compared with one another. The matrix can be used to rank-order the sequences, to search for new sequences, to compare sequences to other quantitative data such as binding energy or distance between binding sites, to distinguish mutations from polymorphisms, to design sequences of a given strength, and to detect errors in databases. The R i method has been used to identify previously undescribed but experimentally verified DNA binding sites. The individual information distribution was determined for E. coli ribosome binding sites, bacterial Fis binding sites, and human donor and acceptor splice junctions, among others. The distributions demonstrate clearly that the consensus sequence is highly unusual, and hence is a poor method to describe naturally occurring binding sites. IS - 4 JF - J Theor Biol SN - 0022-5193 AD - National Cancer Institute, Frederick Cancer Research and Development Center, Laboratory of Mathematical Biology, P.O. Box B, Frederick, MD 21702-1201, USA. toms@ncifcrf.gov EP - 441 TI - Information content of individual genetic sequences. VL - 189 SP - 427 KW - informationtheory KW - sequencealignment KW - statistics AU - Schneider, TD PY - 1997/12/21/ UR - http://view.ncbi.nlm.nih.gov/pubmed/9446751 ER -