W554 Nucleic Acids Research, 2009, Vol. 37, Web Server issue a long motif into several smaller blocks. Insertions or deletions of a large segment are allowed in between blocks, but not allowed within them. For example, the motif ‘H-G-T-x(3)-G-x(77,101)-A-x-G-N-x(57,78)-G- T-S-x(3)-P’ can be decomposed into three motif blocks: ‘H-G-T-x(3)-G’, ‘A-x-G-N’ and ‘G-T-S-x(3)-P’. Each of these blocks can be treated as a small motif, but it should be remembered that these blocks are relevant to each other from the evolutionary point of view. For example, the motif blocks found by the mining server MAGIIC-PRO usually interact or cooperate with each other when proteins are folded or bind to other molecules (9,10). seeMotif can help to discover these relationships. In seeMotif, a block match on the structure chains is assessed by two properties calculated from the local sequence alignment. An index named ‘conservation score’ is deﬁned by the ratio of the number of exact matches and positive substitutions appearing on the non-wildcard positions to the number of all non-wildcard positions of a block in the consensus line of BLAST (32) output. In addition, a block is regarded as ‘broken’ if it is interrupted by a gap ‘ ’ on the reference sequence. Structure selection by homology seeMotif proposes a three-step procedure for structure selection through homology inference. The ﬁrst step of the proposed approach involves pattern matching (described in the subsection ‘Motif expression’) to deter- mine where the motifs are present in the reference sequence. The second step performs local sequence align- ment using BLAST on the reference sequence against the set of protein chains in PDB structures. PDB structures containing at least one protein chain homologous to the reference sequence, deﬁned by e-value <0.001, are then collected by seeMotif. Brieﬂy speaking, for short motifs that might match too many unrelated proteins, this step helps to restrict the target list within homologues of the reference sequence. On the other hand, for longer or more speciﬁc motifs that match rare proteins, employing sequence alignment turns out to collect a larger set of potentially homologous structures for the next step than that obtained by performing conventional pattern matching. With the results of the ﬁrst and the second steps, a potential position mapping between a motif and a PDB chain can be constructed, even when the sequence is incomplete or has been mutated. The third step adopts two constraints to eliminate putative wrong position map- pings: a block that has a conservation score <0.5 or is broken will be excluded in the result page of seeMotif. It should be noticed that the conservation score is calculated for each instance of a block, which means a motif or motif block might be present in one PDB chain but missing in another. This scenario increases the number of PDB structures selected by seeMotif while preserving the visu- alization quality. Structure selection by interaction network Investigations on linear motifs reveal that many of them occur in otherwise unrelated proteins (21). To avoid missing putative structures when visualizing linear motifs, seeMotif provides another way for structure selec- tion that utilizes a pre-constructed protein–protein inter- action (PPI) network based on 7459 PDB complex structures. All the UniProt (33) IDs present in PDB struc- tures with more than one protein chain are collected as vertices of the network, and a link is constructed between two vertexes as long as they co-occur in the same complex. When a user submits a reference sequence, either via a UniProt or PDB ID, seeMotif extracts all of its binding partners in the PPI network and the associated complexes containing any of these binding partners. Afterward, pat- tern matching is performed on all the protein chains from the selected complexes, but not the binding partners of the reference protein. In this way, sequence motifs that have arisen convergently might have chances to be visualized among unrelated proteins for further sequence or struc- tural characterization. WEB INTERFACE In the input page of seeMotif, users can specify the query motifs in a text ﬁeld. Distinct motifs should be separated by a blank space. Various pattern formats, including POSIX regular expression, PROSITE patterns and the entry IDs of motif databases, can be used to specify a sequence motif. Moreover, seeMotif provides a simple format for pointing out a block by positions directly. For example, ‘165–214’ indicates the segment of the refer- ence sequence from its 165th to 214th positions. Motifs described by hidden Markov model (HMM) proﬁles such as that of Pfam (34) or consensus sequences derived from results of multiple sequence alignments should also be speciﬁed in this way. The reference sequence can be spe- ciﬁed in three ways, using a UniProt accession number or entry name, providing a PDB ID along with a chain number, or typing in the protein sequence in FASTA format directly. Moreover, seeMotif accepts the search result pages of databases ELM and MnM or the mining results of MAGIIC-PRO and SLiMDisc as the input by using the technique called bookmarklet. Detailed informa- tion can be found on the web site of seeMotif. Before the result page is presented, seeMotif uses an intermediate web page for reexamining the query and set- ting options. In this page, the users are requested to spec- ify the approach of selecting structures. In the result page, seeMotif maps all the motifs onto the structures collected from PDB through the desired approach. There are two visualization modes in the result page: multi-motif and single-motif. In multi-motif mode, multiple motifs can be visualized simultaneously in distinct colors. It might happen that more than one motif can match the same residues of the reference sequence, resulting in conﬂicts when assigning colors. In this regard, overlaps between motifs should be detected before coloring the residues. In multi-motif mode, only one matched position is considered for each motif block at a time. seeMotif enu- merates all the combinations of motif matching and users can switch among them via a drop-down list. Once the positions of motif blocks are selected, motif blocks that