This document describes the WWW BLAST interface.

     BLAST (Basic Local Alignment Search Tool) is  the  heuristic
     search  algorithm  employed  by the programs blastp, blastn,
     blastx, tblastn, and tblastx; these programs ascribe  signi-
     ficance  to  their findings using the statistical methods of
     Karlin and Altschul (1990, 1993) with  a  few  enhancements.
     The  BLAST  programs  were  tailored for sequence similarity
     searching -- for example to identify  homologs  to  a  query
     sequence.   The programs are not generally useful for motif-
     style searching.  For a discussion of basic issues in  simi-
     larity  searching of sequence databases, see Altschul et al.

     The five BLAST programs described here perform the following

     blastp    compares an amino acid query  sequence  against  a
               protein sequence database;

     blastn    compares a nucleotide  query  sequence  against  a
               nucleotide sequence database;

     blastx    compares  the  six-frame  conceptual   translation
               products  of  a  nucleotide  query  sequence (both
               strands) against a protein sequence database;

     tblastn   compares  a  protein  query  sequence  against   a
               nucleotide     sequence    database    dynamically
               translated  in  all  six  reading   frames   (both

     tblastx   compares the six-frame translations of  a  nucleo-
               tide query sequence against the six-frame transla-
               tions of a nucleotide sequence database.

BLAST Search parameters

Display a histogram of scores for each search; default is yes. (See parameter H in the BLAST Manual).
Restricts the number of short descriptions of matching sequences reported to the number specified; default limit is 100 descriptions. (See parameter V in the manual page). See also EXPECT and CUTOFF.
Restricts database sequences to the number specified for which high-scoring segment pairs (HSPs) are reported; the default limit is 50. If more database sequences than this happen to satisfy the statistical significance threshold for reporting (see EXPECT and CUTOFF below), only the matches ascribed the greatest statistical significance are reported. (See parameter B in the BLAST Manual).
The statistical significance threshold for reporting matches against database sequences; the default value is 10, such that 10 matches are expected to be found merely by chance, according to the stochastic model of Karlin and Altschul (1990). If the statistical significance ascribed to a match is greater than the EXPECT threshold, the match will not be reported. Lower EXPECT thresholds are more stringent, leading to fewer chance matches being reported. Fractional values are acceptable. (See parameter E in the BLAST Manual).
Cutoff score for reporting high-scoring segment pairs. The default value is calculated from the EXPECT value (see above). HSPs are reported for a database sequence only if the statistical significance ascribed to them is at least as high as would be ascribed to a lone HSP having a score equal to the CUTOFF value. Higher CUTOFF values are more stringent, leading to fewer chance matches being reported. (See parameter S in the BLAST Manual). Typically, significance thresholds can be more intuitively managed using EXPECT.
Specify an alternate scoring matrix for BLASTP, BLASTX, TBLASTN and TBLASTX. The default matrix is BLOSUM62 (Henikoff & Henikoff, 1992). The valid alternative choices include: PAM40, PAM120, PAM250 and IDENTITY. No alternate scoring matrices are available for BLASTN; specifying the MATRIX directive in BLASTN requests returns an error response.
Restrict a TBLASTN search to just the top or bottom strand of the database sequences; or restrict a BLASTN, BLASTX or TBLASTX search to just reading frames on the top or bottom strand of the query sequence.
Mask off segments of the query sequence that have low compositional complexity, as determined by the SEG program of Wootton & Federhen (Computers and Chemistry, 1993), or segments consisting of short-periodicity internal repeats, as determined by the XNU program of Claverie & States (Computers and Chemistry, 1993), or, for BLASTN, by the DUST program of Tatusov and Lipman (in preparation). Filtering can eliminate statistically significant but biologically uninteresting reports from the blast output (e.g., hits against common acidic-, basic- or proline-rich regions), leaving the more biologically interesting regions of the query sequence available for specific matching against database sequences.
Low complexity sequence found by a filter program is substituted using the letter "N" in nucleotide sequence (e.g., "NNNNNNNNNNNNN") and the letter "X" in protein sequences (e.g., "XXXXXXXXX"). Users may turn off filtering by using the "Filter" option on the "Advanced options for the BLAST server" page.
Filtering is only applied to the query sequence (or its translation products), not to database sequences. Default filtering is DUST for BLASTN, SEG for other programs.
It is not unusual for nothing at all to be masked by SEG, XNU, or both, when applied to sequences in SWISS-PROT, so filtering should not be expected to always yield an effect. Furthermore, in some cases, sequences are masked in their entirety, indicating that the statistical significance of any matches reported against the unfiltered query sequence should be suspect.
Causes NCBI gi identifiers to be shown in the output, in addition to the accession and/or locus name.


     The fundamental unit of BLAST algorithm output is the  High-
     scoring Segment Pair (HSP).  An HSP consists of two sequence
     fragments of arbitrary but equal length whose  alignment  is
     locally  maximal  and for which the alignment score meets or
     exceeds a threshold or cutoff score.  A set of HSPs is  thus
     defined  by  two  sequences,  a scoring system, and a cutoff
     score; this set may be empty if the cutoff score  is  suffi-
     ciently  high.   In  the programmatic implementations of the
     BLAST algorithm described here, each HSP consists of a  seg-
     ment  from  the  query  sequence  and  one  from  a database
     sequence.  The sensitivity and speed of the programs can  be
     adjusted  via  the standard BLAST algorithm parameters W, T,
     and X (Altschul et al., 1990); selectivity of  the  programs
     can be adjusted via the cutoff score.

     A Maximal-scoring Segment  Pair  (MSP)  is  defined  by  two
     sequences and a scoring system and is the highest-scoring of
     all possible segment pairs that can be produced from the two
     sequences.   The  statistical methods of Karlin and Altschul
     (1990, 1993) are applicable to determining the  significance
     of MSP scores in the limit of long sequences, under a random
     sequence model that assumes independent and identically dis-
     tributed  choices  for  the residues at each position in the
     sequences.  In the programs described here,  Karlin-Altschul
     statistics  have  been extrapolated to the task of assessing
     the significance of HSP scores obtained from comparisons  of
     potentially short, biological sequences.

     The approach to similarity searching taken by the BLAST pro-
     grams  is  first to look for similar segments (HSPs) between
     the query sequence and a database sequence, then to evaluate
     the statistical significance of any matches that were found,
     and finally to report only  those  matches  that  satisfy  a
     user-selectable threshold of significance.  Findings of mul-
     tiple HSPs involving the query sequence and a  single  data-
     base  sequence  may be treated statistically in a variety of
     ways.  By default the programs use "Sum" statistics  (Karlin
     and  Altschul, 1993).  As such, the statistical significance
     ascribed to a set of HSPs may be higher than  that  ascribed
     to any individual member of the set.  Only when the ascribed
     significance  satisfies  the  user-selectable  threshold  (E
     parameter) will the match be reported to the user.

     The task of finding HSPs begins with identifying short words
     of  length  W  in  the  query  sequence that either match or
     satisfy some positive-valued threshold score T when  aligned
     with a word of the same length in a database sequence.  T is
     referred  to  as  the  neighborhood  word  score   threshold
     (Altschul  et  al.,  1990).  These initial neighborhood word
     hits act as seeds for initiating  searches  to  find  longer
     HSPs  containing  them.   The word hits are extended in both
     directions along each sequence for as far as the  cumulative
     alignment  score  can  be  increased.  Extension of the word
     hits in each direction  are  halted  when:   the  cumulative
     alignment score falls off by the quantity X from its maximum
     achieved value; the cumulative score goes to zero or  below,
     due  to  the  accumulation  of  one or more negative-scoring
     residue  alignments;  or  the  end  of  either  sequence  is


     From Karlin and  Altschul  (1990),  the  principal  equation
     relating  the  score  of an HSP to its expected frequency of
     chance occurrence is:

                        E = K N exp(-Lambda S)

     where E is the expected frequency of chance occurrence of an
     HSP having score S (or one scoring higher); K and Lambda are
     Karlin-Altschul parameters; N is the product  of  the  query
     and  database  sequence  lengths,  or the size of the search
     space; and exp is the exponentiation function.

     Lambda may be thought of as the expected increase in  relia-
     bility  of  an  alignment associated with a unit increase in
     alignment score.  Reliability in this case is  expressed  in
     units  of  information,  such  as bits or nats, with one nat
     being equivalent to 1/log(2) (roughly 1.44) bits.

     The expectation E (range 0 to infinity)  calculated  for  an
     alignment between the query sequence and a database sequence
     can be  extrapolated  to  an  expectation  over  the  entire
     database search, by converting the pairwise expectation to a
     probability (range 0-1) and multiplying the  result  by  the
     ratio of the entire database size (expressed in residues) to
     the length of the matching database sequence.  In detail:

                   E_database = (1 - exp(-E)) D / d

     where D is the size of the database; d is the length of  the
     matching  database  sequence; and the quantity (1 - exp(-E))
     is the probability, P, corresponding to  the  expectation  E
     for  the  pairwise  sequence  comparison.   Note that in the
     limit of infinite E, P approaches 1; and in the limit  as  E
     approaches  0, E and P approach equality.  Due to inaccuracy
     in the statistical methods as they are applied in the  BLAST
     programs, whenever E and P are less than about 0.05, the two
     values can be practically treated as being equal.

     In contrast to the random sequence  model  used  by  Karlin-
     Altschul statistics, biological sequences are often short in
     length -- an HSP may involve a relatively large fraction  of
     the  query or database sequence, which reduces the effective
     size of the 2-dimensional search space defined  by  the  two
     sequences.   To obtain more accurate significance estimates,
     the BLAST programs compute effective lengths for  the  query
     and database sequences that are their real lengths minus the
     expected length of the HSP, where the expected length for an
     HSP is computed from its score.  In no event is an effective
     length for the query or database sequence  permitted  to  go
     below  1.  Thus, the effective length of either the query or
     the database sequence is computed according to  the  follow-

          Length_eff = MAX( Length_real - Lambda S / H , 1)

     where H is the relative entropy of the target and background
     residue  frequencies (Karlin and Altschul, 1990), one of the
     statistics reported by the BLAST programs.  H may be thought
     of as the information expected to be obtained from each pair
     of aligned residues in a real alignment  that  distinguishes
     the alignment from a random one.


     The default scoring matrix used by blastp, blastx,  tblastn,
     and  tblastx  is the BLOSUM62 matrix (Henikoff and Henikoff,

     Several PAM (point  accepted  mutations  per  100  residues)
     amino  acid  scoring  matrices  are  provided  in  the BLAST
     software distribution,  including  the  PAM40,  PAM120,  and
     PAM250.  While the BLOSUM62 matrix is a good general purpose
     scoring matrix and is the default matrix used by  the  BLAST
     programs,  if  one  is  restricted to using only PAM scoring
     matrices, then the PAM120 is recommended for general protein
     similarity  searches  (Altschul,  1991).  The pam(1) program
     can be used to produce PAM matrices of any desired iteration
     from  2  to  511.   Each matrix is most sensitive at finding
     similarities at  its  particular  PAM  distance.   For  more
     thorough searches, particularly when the mutational distance
     between potential homologs is unknown and  the  significance
     of  their  similarity  may be only marginal, Altschul (1991,
     1992) recommends performing at  least  three  searches,  one
     each with the PAM40, PAM120 and PAM250 matrices.

     In blastn, the M parameter sets the reward score for a  pair
     of matching residues; the N parameter sets the penalty score
     for mismatching residues.  M and  N  must  be  positive  and
     negative integers, respectively.  The relative magnitudes of
     M and N determines the number of nucleic  acid  PAMs  (point
     accepted mutations per 100 residues) for which they are most
     sensitive  at  finding  homologs.   Higher  ratios  of   M:N
     correspond to increasing nucleic acid PAMs (increased diver-
     gence).  The default values for M and N, respectively 5  and
     -4,  having  a ratio of 1.25, correspond to about 47 nucleic
     acid PAMs, or about 58 amino acid PAMs; an M:N  ratio  of  1
     corresponds  to  30 nucleic acid PAMs or 38 amino acid PAMs.
     At higher than about 40 nucleic acid PAMs, or 50 amino  acid
     PAMs,  better  sensitivity at detecting similarities between
     coding regions is expected by performing comparisons at  the
     amino  acid  level (States et al., 1991), using conceptually
     translated nucleotide sequences (re:  blastx,  tblastn,  and

     Independent of the values chosen for M and  N,  the  default
     wordlength  W=11  used  by  blastn  restricts the program to
     finding sequences that share at least an 11-mer  stretch  of
     100%  identity  with  the  query.  Under the random sequence
     model, stretches of 11  consecutive  matching  residues  are
     unlikely  to  occur  merely  by  chance  even  between  only
     moderately diverged homologs.  Thus, blastn with its default
     parameter  settings is poorly suited to finding anything but
     very similar sequences.  If better  sensitivity  is  needed,
     one should use a smaller value for W.

     For the blastn program, it may be easy to see how  multiply-
     ing both M and N by some large number will yield proportion-
     ally larger alignment scores with their statistical signifi-
     cance  remaining  unchanged.  This scale-independence of the
     statistical significance estimates from blastn has its  ana-
     log  in  the  scoring  matrices used by the other BLAST pro-
     grams:  multiplying all elements in a scoring matrix  by  an
     arbitrary  factor  will  proportionally  alter the alignment
     scores but will not  alter  their  statistical  significance
     (assuming  numerical precision is maintained).  From this it
     should be clear that raw alignment  scores  are  meaningless
     without  specific  knowledge  of the scoring matrix that was


     Regardless of the scoring  scheme  employed,  two  stringent
     criteria  must  be  met in order to be able to calculate the
     Karlin-Altschul parameters Lambda and K.  First,  given  the
     residue  composition  for the query sequence and the residue
     composition assumed for the database,  the  alignment  score
     expected  for  any  randomly  selected pair of residues (one
     from the query sequence and one from the database)  must  be
     negative.   Second,  given the sequence residue compositions
     and the scoring scheme, a positive score must be possible to
     achieve.   For  instance,  the  match reward score of blastn
     must have a positive value; and given the assumption made by
     blastn  that the 4 nucleotides A, C, G and T are represented
     at equal 25% frequencies in the database, a  wide  range  of
     value  combinations  for  M  and N are precluded from use --
     namely those combinations where the magnitude of  the  ratio
     M:N is greater than or equal to 3.


     The parameter C can be set to a positive integer  to  select
     the  genetic code that will be used by blastx and tblastx to
     translate the query sequence.  The -dbgcode parameter can be
     used  to select an alternate genetic code for translation of
     the database by the programs tblastn and tblastx.   In  each
     case,  the  default genetic code is the so-called "Standard"
     or "Universal" genetic code.  To obtain  a  listing  of  the
     genetic codes available and their associated numerical iden-
     tifiers, invoke blastx or  tblastx  with  the  command  line
     parameter C=list. Note:  the numerical identifiers used here
     for  genetic  codes  parallel  those  defined  in  the  NCBI
     software  Toolbox;  hence  some  numerical  values  will  be
     skipped as genetic codes are updated.

     The list of genetic codes  available  and  their  associated
     values for the parameters C and -dbgcode are:

     1 Standard or Universal

     2 Vertebrate Mitochondrial

     3 Yeast Mitochondrial

     4   Mold,   Protozoan,   Coelenterate   Mitochondrial    and

     5 Invertebrate Mitochondrial

     6 Ciliate Macronuclear

     9 Echinodermate Mitochondrial

     10 Alternative Ciliate Macronuclear

     11 Eubacterial

     12 Alternative Yeast

     13 Ascidian Mitochondrial

     14 Flatworm Mitochondrial


     The Expect and P-values reported for HSPs are  dependent  on
     several factors including:  the scoring system employed, the
     residue composition of the query sequence, an assumed  resi-
     due  composition for a typical database sequence, the length
     of the query sequence, and the total length of the database.
     HSP  scores from different program invocations are appropri-
     ate for comparison even if the  databases  searched  are  of
     different  lengths,  as  long as the other factors mentioned
     here do  not  vary.   For  example,  alignment  scores  from
     searches  with  the  default  BLOSUM62  matrix should not be
     directly compared  with  scores  obtained  with  the  PAM120
     matrix;  and  scores produced using two versions of the same
     PAM matrix, each created to different  scales  (see  above),
     can  not  be meaningfully compared without conversion to the
     same scale.

     Some isolation from the many factors involved  in  assessing
     the  statistical  significance  of  HSPs  can be attained by
     observing the information content reported (in bits) for the
     alignments.   While  the  information  content of an HSP may
     change when different scoring systems are used  (e.g.,  with
     different  PAM matrices), the number of bits reported for an
     HSP will at least be independent of the scale to  which  the
     scoring  matrix was generated.  (In practice, this statement
     is not quite true, because the alignment scores used by  the
     BLAST  programs  are integers that lack much precision).  In
     other words, when conveying the statistical significance  of
     an  alignment,  the  alignment  score  itself  is not useful
     unless the specific scoring matrix that was employed is also
     provided, but the informativeness of an alignment is a mean-
     ingful statistic that can be  used  to  ascribe  statistical
     significance  (a  P-value)  to  the  match  independently of
     specific knowledge about the scoring matrix.


     The BLAST programs all provide information  in  roughly  the
     same  format.   First  comes (A) an introduction to the pro-
     gram; (B) a histogram of expectations (see above) if one was
     requested; (C) a series of one-line descriptions of matching
     database sequences; (D) the actual sequence alignments;  and
     finally  the parameters and other statistics gathered during
     the search.

     Sample blastp output from comparing pir|A01243|DXCH  against
     the SWISS-PROT database is presented below.

  A. Program Introduction
     The introductory output provides the program name (BLASTP in
     this  case),  the version number (1.4.6MP in this case), the
     date the program  source  code  last  changed  substantially
     (June  13,  1994), the date the program was built (Sept. 22,
     1994), and a description of the query sequence and  database
     to be searched.  These may all be important pieces of infor-
     mation if a  bug  is  suspected  or  if  reproducibility  of
     results is important.

     The "Searching..." indicator  indicates  progress  that  the
     program made in searching the database.  A complete database
     search will yield 50 periods (.), or one period per database
     sequence,  whichever  number  is  smaller.  When searching a
     database consisting of 50 sequences or more, if  fewer  than
     50  periods  are  displayed and the program aborted for some
     reason, dividing the number of periods by 0.5 will yield the
     approximate  percentage  (0-100%)  of  the database that was
     searched before the program died.  If the program had diffi-
     culty  making  progress  through  the  database, one or more
     asterisks (*) may be interspersed  between  the  periods  at
     one-minute intervals.

  B. Histogram of Expectations
     Shown in the output below is a histogram of the lowest (most
     significant)  Expect  values  obtained  with  each  database
     sequence.  This information is  useful  in  determining  the
     numbers  of  database  sequences  that achieved a particular
     level of statistical significance.  It indicates the  number
     of database matches that would be reportable at various set-
     tings for the expectation threshold (E parameter).

  C. One-line Summaries
     The one-line sequence descriptions and summaries of  results
     are useful for identifying biologically interesting database
     matches and correlating this interest with  the  statistical
     significance  estimates.   Unless  otherwise  requested, the
     database sequences are sorted by increasing P-value  (proba-
     bility).   Identifiers  for the database sequences appear in
     the first column;  then  come  brief  descriptions  of  each
     sequence,  which may need to be truncated in order to fit in
     the available space.  The "High Score" column  contains  the
     score  of  the  highest-scoring HSP found with each database
     sequence.  The "P(N)" column  contains  the  lowest  P-value
     ascribed  to any set of HSPs for each database sequence; and
     the "N" column displays the number of HSPs in the set  which
     was  ascribed  the lowest P-value.  The P-values are a func-
     tion of N, as used in Karlin-Altschul  "Sum"  statistics  or
     Poisson  statistics, to treat situations where multiple HSPs
     are found.  It should be noted that the highest-scoring  HSP
     whose  score  is  reported in the "High Score" column is not
     necessarily a member of the set of  HSPs  which  yields  the
     lowest P-value; the highest-scoring HSP may be excluded from
     this set on the basis of  consistency  rules  governing  the
     grouping  of HSPs (see the -consistency option).  Numbers of
     the form "7.7e-160" are in  scientific  notation.   In  this
     particular  example,  the  number  being  represented is 7.7
     times 10 to the minus 160th power.  which is  astronomically
     close to zero.

  D. Alignments
     Alignments found with  the  BLAST  algorithm  are  ungapped.
     Several  statistics  are used to describe each HSP:  the raw
     alignment Score; the raw score converted to bits of informa-
     tion  by  multiplying by Lambda (see the Statistics output);
     the number of times one might Expect to see such a match (or
     a  better one) merely by chance; the P-value (probability in
     the range 0-1) of observing such a  match;  the  number  and
     fraction  of  total residues in the HSP which are identical;
     the number and fraction of residues for which the  alignment
     scores  have positive values.  When Sum statistics have been
     used to calculate the Expect and P-values,  the  P-value  is
     qualified  with  the  word "Sum" and the N parameter used in
     the Sum statistics is provided in  parentheses  to  indicate
     the  number of HSPs in the set; when Poisson statistics have
     been used to calculate the Expect and P-values, the  P-value
     is qualified with the word "Poisson".  Between the two lines
     of Query and Subject (database) sequence is a line  indicat-
     ing  the  specific  residues which are identical, as well as
     those which are non-identical but nevertheless have positive
     alignment scores defined in the scoring matrix that was used
     (the BLOSUM62 matrix in this case).   Identical  letters  or
     residues,  when  paired with each other, are not highlighted
     if their alignment score is negative or zero.   Examples  of
     this  would  be  an X juxtaposed with an X in two amino acid
     sequences, or an N juxtaposed with another N in two  nucleo-
     tide sequences.  Such ambiguous residue-residue pairings may
     be uninformative and thus lend no  support  to  the  overall
     alignment being either real or random; however, the informa-
     tiveness of these pairings is left up to  the  user  of  the
     BLAST  programs to decide, because any values desired can be
     specified in a scoring matrix of the user's own making.

     BLASTP 1.4.6MP [13-Jun-94] [Build 13:58:36 Sep 22 1994]

     Reference:  Altschul, Stephen F., Warren Gish, Webb Miller, Eugene W. Myers,
     and David J. Lipman (1990).  Basic local alignment search tool.  J. Mol. Biol.

     Query =  pir|A01243|DXCH  232 Gene X protein - Chicken (fragment)
             (232 letters)

     Database:  SWISS-PROT Release 29.0
                38,303 sequences; 13,464,008 total letters.

          Observed Numbers of Database Sequences Satisfying
          Various EXPECTation Thresholds (E parameter values)

             Histogram units:      = 31 Sequences     : less than 31 sequences

      EXPECTation Threshold
      (E parameter)
         V   Observed Counts-->
       10000 4863 1861 |============================================================
        6310 3002  782 |=========================
        3980 2220  812 |==========================
        2510 1408  303 |=========
        1580 1105  393 |============
        1000  712  179 |=====
         631  533  161 |=====
         398  372   80 |==
         251  292   73 |==
         158  219   50 |=
         100  169   32 |=
        63.1  137   18 |:
        39.8  119    9 |:
        25.1  110    6 |:
        15.8  104    9 |:
      >>>>>>>>>>>>>>>>>>>>>  Expect = 10.0, Observed = 95  <<<<<<<<<<<<<<<<<
        10.0   95    4 |:
        6.31   91    3 |:
        3.98   88    1 |:
        2.51   87    3 |:
        1.58   84    0 |
        1.00   84    2 |:

                                                                   High  Probability
     Sequences producing High-scoring Segment Pairs:              Score  P(N)      N

     sp|P01013|OVAX_CHICK GENE X PROTEIN (OVALBUMIN-RELATED) (...  1191  7.7e-160  1
     sp|P01014|OVAY_CHICK GENE Y PROTEIN (OVALBUMIN-RELATED).       949  7.0e-127  1
     sp|P01012|OVAL_CHICK OVALBUMIN (PLAKALBUMIN).                  645  3.4e-100  2
     sp|P19104|OVAL_COTJA OVALBUMIN.                                626  1.2e-96   2
     sp|P05619|ILEU_HORSE LEUKOCYTE ELASTASE INHIBITOR (LEI).       216  3.7e-71   3
     sp|P80229|ILEU_PIG   LEUKOCYTE ELASTASE INHIBITOR (LEI) (...   325  4.0e-71   2
     sp|P29508|SCCA_HUMAN SQUAMOUS CELL CARCINOMA ANTIGEN (SCC...   439  3.5e-70   2
     sp|P30740|ILEU_HUMAN LEUKOCYTE ELASTASE INHIBITOR (LEI) (...   211  1.3e-66   3
     sp|P05120|PAI2_HUMAN PLASMINOGEN ACTIVATOR INHIBITOR-2, P...   176  1.8e-65   4
     sp|P35237|PTI_HUMAN  PLACENTAL THROMBIN INHIBITOR.             473  1.3e-61   1
     sp|P29524|PAI2_RAT   PLASMINOGEN ACTIVATOR INHIBITOR-2, T...   183  9.4e-61   4
     sp|P12388|PAI2_MOUSE PLASMINOGEN ACTIVATOR INHIBITOR-2, M...   179  1.8e-60   4
     sp|P36952|MASP_HUMAN MASPIN PRECURSOR.                         198  2.6e-58   4
     sp|P32261|ANT3_MOUSE ANTITHROMBIN-III PRECURSOR (ATIII).       142  4.0e-48   5
     sp|P01008|ANT3_HUMAN ANTITHROMBIN-III PRECURSOR (ATIII).       122  7.5e-48   5

     WARNING:  Descriptions of 80 database sequences were not reported due to the
               limiting value of parameter V = 15.

       ... alignments with the top 8 database sequences deleted ...

                 (MONOCYTE ARG- SERPIN).
                 Length = 415

      Score = 176 (80.2 bits), Expect = 1.8e-65, Sum P(4) = 1.8e-65
      Identities = 38/89 (42%), Positives = 50/89 (56%)

                  +I +LL   S D DT +VLVNA+YFKG WKT F  +     PF V   +  PVQMM +

                    N+  +   K +ILELP+A      L+L

      Score = 165 (75.2 bits), Expect = 1.8e-65, Sum P(4) = 1.8e-65
      Identities = 33/78 (42%), Positives = 47/78 (60%)

                  AN +G+S    L +S+  H A ++++E+G E A  TG +   +      QF ADHPFLFL

     Query:   215 IKHNPTNTIVYFGRYWSP 232
                  I H  T  I++FGR+ SP
     Sbjct:   398 IMHKITKCILFFGRFCSP 415

      Score = 144 (65.6 bits), Expect = 1.8e-65, Sum P(4) = 1.8e-65
      Identities = 26/62 (41%), Positives = 41/62 (66%)

                  + D  + LE +E  I ++KL +WT+ + M +  V+VY+PQ K+EE Y L S+L ++GM D

     Query:   150 LF 151
     Sbjct:   332 AF 333

      Score = 61 (27.8 bits), Expect = 1.8e-65, Sum P(4) = 1.8e-65
      Identities = 10/17 (58%), Positives = 16/17 (94%)

     Query:    81 SGDLSMLVLLPDEVSDL 97
                  +GD+SM +LLPDE++D+
     Sbjct:   259 AGDVSMFLLLPDEIADV 275

     WARNING:  HSPs involving 86 database sequences were not reported due to the
               limiting value of parameter B = 9.



       Query                        -----  As Used  -----    -----  Computed  ----
       Frame  MatID Matrix name     Lambda    K       H      Lambda    K       H
        +0      0   BLOSUM62        0.316   0.132   0.370    same    same    same

       Frame  MatID  Length  Eff.Length   E    S W   T  X     E2  S2
        +0      0      232       232      10. 57 3  11 22    0.22 33

       Query          Expected         Observed           HSPs       HSPs
       Frame  MatID  High Score       High Score       Reportable  Reported
        +0      0    62 (28.2 bits)  1191 (542.5 bits)     330         24

       Query         Neighborhd  Word      Excluded    Failed   Successful  Overlaps
       Frame  MatID   Words      Hits        Hits    Extensions Extensions  Excluded
        +0      0      4988     5661199     1146395     4504598    10187        13

       Database:  SWISS-PROT Release 29.0
         Release date:  June 1994
         Posted date:  1:29 PM EDT Jul 28, 1994
       # of letters in database:  13,464,008
       # of sequences in database:  38,303
       # of database sequences satisfying E:  95
       No. of states in DFA:  561 (55 KB)
       Total size of DFA:  110 KB (128 KB)
       Time to generate neighborhood:  0.03u 0.01s 0.04t  Real: 00:00:00
       No. of processors used:  8
       Time to search database:  32.27u 0.78s 33.05t  Real: 00:00:04
       Total cpu time:  32.33u 0.91s 33.24t  Real: 00:00:05



     This work is in the public domain.


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