W54 Nucleic Acids Research, 2009, Vol. 37, Web Server issue which features an improved FOM calculation, and returns a list of hits rank-ordered by their FOM to the users inter- actively as well as through email. METHODS Overview of the SIB algorithm PSI-BLAST achieves its high sensitivity for remote homo- logs by performing multiple rounds of searches. At each iteration, PSI-BLAST attempts to build a better model of its original query sequence using homologous sequences found in previous rounds. Thus, the earlier iterations (namely iteration one and two) are highly speciﬁc, ﬁnding mostly close homologs—but not very sensitive. In later iterations, more weakly related homologs are found, which are then used to build models for the even more remote homologs, imparting PSI-BLAST with the sensi- tivity needed for detecting the more remote homologs. However, these weakened relationships and diminishing similarities between sequences increase the probability of incorporating a non-homologous sequence into the model, leading to model corruption and the false identiﬁcation of non-homologous sequences as putative homologs. As described in the initial report of this algorithm, the SIB algorithm is built on the rationale that the beneﬁts of low model corruption from early rounds of PSI-BLAST and the high sensitivity from later rounds can both be reaped by combining results from these iterations. Thus, the hits from the ﬁnal round can be validated against those of earlier rounds, which in turn, would lead to improved discrimination of true and false positives. Toward this end, SIB uses a mathematical formulation (13) that com- bines the reported E-values of each ‘overlapped’ hit from the two PSI-BLAST iterations to calculate the FOM. This FOM serves the same role as the E-value reported by PSI-BLAST in the sense that it indicates the statistical signiﬁcance of the hits relative to one another. For the FOM to be a true E-value, however, the underlying sta- tistical independence of the two iterations assumption of the FOM formulation has to be fulﬁlled. In our original FOM formulation, the E-values of the two iterations were converted to P-values. Under statisti- cal independence, our assumption to combine P-values was to simply multiply the two P-values. This combined P-value was then converted to a FOM that was mathe- matically analogous to the ‘E’-value reported by PSI- BLAST. Recently, we have become aware that Bailey and Gribskov (15) have determined that the correct equa- tion for calculating the combined P-value of two indepen- dent values should in fact be Ptot ¼ P2Pf ð1 logðP2PfÞÞ where P2 and Pf are the P-values for iteration 2 and the ﬁnal iteration, respectively. This new equation for calcu- lating the combined P-value has been incorporated into the SIB algorithm running on the SIB-BLAST web server described below. The performance of the original SIB algorithm was directly veriﬁed using the same 103 sequences from the Aravind ‘gold standard’ dataset (3,14) used by the PSI-BLAST developers. The evaluation results indicated that SIB exhibits higher speciﬁcity and sensitivity than that of PSI-BLAST for near identical computational time and a comparable performance to SAM-T2K using much less time. We have veriﬁed that the error versus coverage plot remains essentially unchanged after incor- porating the new method of combining two P-values as expected since the new formula is still a monotonous function of P2Pf. SIB-BLAST Web server SIB-BLAST is comprised of the following steps: (i) per- forming a PSI-BLAST search of a query protein sequence against the non-redundant (NR) database; (ii) comparing resultant hits found in iteration 2 and the last iteration; (iii) calculating a FOM for each hit by combining its cor- responding E-values at iteration 2 and at the ﬁnal round; and (iv) re-ranking the merged list of hits according to their FOM. The SIB-BLAST web server (Figure 1A) requests three inputs from the user: a protein sequence in FASTA format, the number of iterations of the PSI-BLAST search and the maximal number of target sequences reported in the PSI-BLAST search. Users are given the option to either paste a protein sequence or upload a ﬁle containing a protein sequence in FASTA format. The number of PSI-BLAST iterations to be performed is lim- ited to be between 3 to 10 rounds, though users are advised to choose no more than ﬁve to six iterations as suggested by the PSI-BLAST developers (3). The number of target sequences reported by PSI-BLAST can be chosen as 1000, 2000, 5000, 10 000 or 20 000. This number is pur- posefully restricted to be higher than the PSI-BLAST default value to ensure that even weak hits are reported in the individual rounds as they might become signiﬁcant once results from diﬀerent rounds are combined. Other than these three user-deﬁned input parameters, the parameters used to conduct the search are preset. The NR database (updated weekly) is used for querying the sequence. The algorithm parameter for the Expect threshold, which reports the number of sequence matches, is set to 1000 instead of PSI-BLAST’s default value of 10. This higher threshold is to ensure that those true but more distant homologs identiﬁed in the ﬁnal iteration but having very large E-value in round two are reported in both lists of iterations, which are subjected to down- stream SIB processing. All other algorithm parameters, such as the word size, the scoring matrix and PSI- BLAST threshold E-value of 0.002 for inclusion of matches in the proﬁle for the next round are set to default values. Users are asked to provide an email address to which their results will be forwarded. Alternatively, users can bookmark the result link to obtain the output interactively when it is available. A status page, which shows the prog- ress of the SIB-BLAST job is displayed upon submission. SIB-BLAST outputs (Figure 1B) a combined list of hits from the second iteration and the last iteration rank-ordered by their corresponding FOM. Based on an analysis on the FOM’s coverage versus error curve on the