INPUT Protein Sequence BLAST Cascade Swissprot (1) nothing found Hypothethical protein found SpTrembl (2) nothing found Hypothethical protein found RefSeq (3) nothing found Comparison for Similar HITS (4) FINAL XML Nucleic Acids Research, 2007, Vol. 35, Web Server issue W447 Program Flow Detail for each BLAST (1) | (2) | (3) 85% < identity < 0% Blast against qpercent & qpercent > 80% Similar HIT database or (1) | (2) | (3) No HIT identity > 98% qpercent & qpercent = 100% 98% < identity < 85% qpercent & qpercent > 80% Identical HIT Hypothethical protein found? No search Database ID in EnsEMBL Succesful Check Homologous HITS Save the Hit Yes NOT successful Succesful identity > 98% Report of Current DB, Ensembl DB Alignment Info Ensembl check EnsEMBL BLAST query: Identical HIT Best HIT Sequence comparison WATER Identical Hit vs Ensembl Best hit Back to BLAST Cascade No Hypothethical protein found? Homologous HIT Yes Save the Hit Back to NOT BLAST Cascade successful identity < 98% Report of Current DB, Alignment Info Comparison for Similar Hits Detail (4) qpercent & qpercent > 80% Similar HITS Swissprot Similar HITS SpTrembl Similar HITS Refseq 60% - 85% identity -> similar 40% - 60% identity -> weakly similar 20% - 40% identity -> putative Merge Results Select the BEST HIT Figure 2. Task ﬂow of Protsweep. In principle, it is possible to decide the signiﬁcance of a match upon its E-value. However, there are a few complications such as that there is no analytical results available for accurately determining E-values for gapped alignments, especially proﬁle HMM alignments. We use as threshold the trusted cut-oﬀ value (TC) existing for each PFAM family. This value is the lowest score for sequences included in the family (e.g. in the full alignment). Therefore, we consider a hit very signiﬁcant if scores better than the trusted cut-oﬀ and at the same time has a signiﬁcant E-value. In the case of SCOP, individual protein families are described by several HMMs. We use the SCOP ﬁltering mechanism to look for consistency in the HMMScan output, and ﬁltering out inconsistent hits. In the case of SMART we use only the E-value. For each of the protein/domain databases used, we have established diﬀerent thresholds and rules. Afterwards DomainSweep takes all true positive hits of all individual database searches for further data inter- pretation. Domain hits are listed as ‘signiﬁcant’: (i) If two or more hits belong to the same INTERPRO family. The task compares all true positive hits of the diﬀerent protein family databases grouping together those hits, which are members of the same INTERPRO family/domain. (ii) If the motif shows the same order as described in PRINTS or BLOCKS. Both databases characterize a protein family with a group of highly conserved motifs/segments in a well-deﬁned order. The task compares the order of the identiﬁed true positive hits with the order described in the corresponding PRINTS or BLOCKS entry. Only hits in correct order are accepted. All other true positive hits are listed as ‘putative’ (Figure 3). It is clear that any automatically produced sequence analysis implies a reasonable compromise between sensitivity and selectivity, and that no ideal recognition threshold exists that would allow for perfect separation of true and false similarities. Our thresholds tend to be rather conservative and stringent and thus the possibility of extending false positives is very limited. The output in the web consists of two groups of graphs, those corresponding to the signiﬁcant and putative hits, and one table output containing all reported protein domains (Supplementary Figure 2). The graphical outputs display for each ‘signiﬁcant’ or ‘putative’ hit a cartoon of