Biomedical subjects

Kiyoko F Aoki

Publications and source records attributed to Kiyoko F Aoki.

5 recordsLinked to original sources

PubMed2004

A score matrix to reveal the hidden links in glycans.

MOTIVATION: Glycans are the third major class of biomolecules following DNA and proteins. They are extremely vital for the functioning of multicellular organisms. However, comparing the fast development of sequence analysis techniques, informatics work on glycans have a long way to go. Alignment algorithms for glycan tree structures are one of the foremost concerns. In addition, the statistical analysis of these algorithms in terms of biological significance needs to be addressed. RESULTS: We developed a tree-structure alignment algorithm for glycans and performed a statistical analysis of these alignment scores such that biologically interesting features could be captured into a score matrix for glycans. We generated our score matrix in a manner similar to BLOSUM, but with slight variations to accomodate our glycan data, including the incorporation of linkage information. We verified the effectiveness of our new glycan score matrix by illustrating how well the resulting score matrix entries correspond with biological knowledge. Future work for even better improvements with the use of a variety of score matrices for different subclasses of glycans due to their complexity is also discussed. CONTACT: mami@kuicr.kyoto-u.ac.jp SUPPLEMENTARY INFORMATION: The glycan score matrix can be downloaded from http://kanehisa.kuicr.kyoto-u.ac.jp/Paper/kcam/glycanMatrix0.1.txt.

Algorithms↗

PubMed2004

The evolutionary repertoires of the eukaryotic-type ABC transporters in terms of the phylogeny of ATP-binding domains in eukaryotes and prokaryotes.

ABC (ATP-binding cassette) transporters play an important role in the communication of various substrates across cell membranes. They are ubiquitous in prokaryotes and eukaryotes, and eukaryotic types (EK-types) are distinguished from prokaryotic types (PK-types) in terms of their genes and domain organizations. The EK-types and PK-types mainly consist of exporters and importers, respectively. Prokaryotes have both the EK-types and the PK-types. The EK-types in prokaryotes are usually called "bacterial multidrug ABC transporters," but they are not well characterized in comparison with the multidrug ABC transporters in eukaryotes. Thus, an exhaustive search of the EK-types among diverse organisms and detailed sequence classification and analysis would elucidate the evolutionary history of EK-types. It would also help shed some light on the fundamental repertoires of the wide variety of substrates through which multidrug ABC transporters in eukaryotes communicate. In this work, we have identified the EK-type ABC transporters in 126 prokaryotes using the profiles of the ATP-binding domain (NBD) of the EK-type ABC transporters from 12 eukaryotes. As a result, 11 clusters were identified from 1,046 EK-types ABC transporters. In particular, two large novel clusters emerged, corresponding to the bacterial multidrug ABC transporters related to the ABCB and ABCC families in eukaryotes, respectively. In the genomic context, most of these genes are located alone or adjacent to genes from the same clusters. Additionally, to detect functional divergences in the NBDs, the Kullback-Leibler divergence was measured among these bacterial multidrug transporters. As a result, several putative functional regions were identified, some corresponding to the predicted secondary structures. We also analyzed a phylogeny of the EK-type ABC transporters in both prokaryotes and eukaryotes, which revealed that the EK-type ABC transporters in prokaryotes have certain repertoires corresponding to the conventional ABC protein groups in eukaryotes. On the basis of these findings, we propose an updated evolutionary hypothesis in which the EK-type ABC transporters in both eukaryotes and prokaryotes consisted of several kinds of ABC transporters in putative ancestor cells before the divergence of eukaryotic and prokaryotic cells.

ATP-Binding Cassette Transporters↗

PubMed2004

Application of a new probabilistic model for recognizing complex patterns in glycans.

MOTIVATION: The study of carbohydrate sugar chains, or glycans, has been one of slow progress mainly due to the difficulty in establishing standard methods for analyzing their structures and biosynthesis. Glycans are generally tree structures that are more complex than linear DNA or protein sequences, and evidence shows that patterns in glycans may be present that spread across siblings and into further regions that are not limited by the edges in the actual tree structure itself. Current models were not able to capture such patterns. RESULTS: We have applied a new probabilistic model, called probabilistic sibling-dependent tree Markov model (PSTMM), which is able to inherently capture such complex patterns of glycans. Not only is the ability to capture such patterns important in itself, but this also implies that PSTMM is capable of performing multiple tree structure alignments efficiently. We prove through experimentation on actual glycan data that this new model is extremely useful for gaining insight into the hidden, complex patterns of glycans, which are so crucial for the development and functioning of higher level organisms. Furthermore, we also show that this model can be additionally utilized as an innovative approach to multiple tree alignment, which has not been applied to glycan chains before. This extension on the usage of PSTMM may be a major step forward for not only the structural analysis of glycans, but it may consequently prove useful for discovering clues into their function.

Algorithms↗

PubMed2004

KCaM (KEGG Carbohydrate Matcher): a software tool for analyzing the structures of carbohydrate sugar chains.

KCaM (KEGG Carbohydrate Matcher) is a tool for the analysis of carbohydrate sugar chains, or glycans. It consists of a web-based graphical user interface that allows users to enter glycans easily with the mouse. The glycan structure is then transformed into our KCF (KEGG Chemical Function) file format and sent to our program which implements an efficient tree-structure alignment algorithm, similar to sequence alignment algorithms but for branched tree structures. Users can also retrieve glycan tree structures in KCF format from their local computers for visualization over the web. The tree-matching algorithm provides several options for performing different types of tree-matching procedures on glycans. These options consist of whether to incorporate gaps in a match, whether to take the linkage information into consideration and local versus global alignment. The results of this program are returned as a list of glycan structures in order of similarity based on these options. The actual alignment can be viewed graphically, and the annotation information can also be viewed easily since all this information is linked with KEGG's comprehensive suite of genomic data. Analogously to BLAST, users are thus able to compare glycan structures of interest with glycans from different glycan databases using a variety of tree-alignment options. KCaM is currently available at http://glycan.genome.ad.jp.

Algorithms↗

PubMed2003

Efficient tree-matching methods for accurate carbohydrate database queries.

One aspect of glycome informatics is the analysis of carbohydrate sugar chains, or glycans, whose basic structure is not a sequence, but a tree structure. Although there has been much work in the development of sequence databases and matching algorithms for sequences (for performing queries and analyzing similarity), the more complicated tree structure of glycans does not allow a direct implementation of such a database for glycans, and further, does not allow for the direct application of sequence alignment algorithms for performing searches or analyzing similarity. Therefore, we have utilized a polynomial-time dynamic programming algorithm for solving the maximum common subtree of two trees to implement an accurate and efficient tool for finding and aligning maximally matching glycan trees. The KEGG Glycan database for glycan structures released recently incorporates our tree-structure alignment algorithm with various parameters to adapt to the needs of a variety of users. Because we use similarity scores as opposed to a distance metric, our methods are more readily used to display trees of higher similarity. We present the two methods developed for this purpose and illustrate its validity.

Algorithms↗