their application spans a wide range of problems such as phylogeny reconstruction , protein functional site detection , and protein and rna structure prediction ( 1 ) .
the research literature is abundant with programs and benchmarks for multiple sequence alignment , particularly for protein data .
traditionally , clustalw ( 2 ) is the most popular program used for multiple sequence alignment ; while balibase ( 3 ) is a likely the most commonly used benchmark of protein alignments .
mafft , probcons and probalign are recent alignment strategies that are among recent programs with the highest accuracies on balibase and other common benchmarks ( i.e. homstrad ( 4 ) and oxbench ( 5 ) . both probcons ( 6 ) and probalign ( 7 ) compute maximal expected accuracy alignments using posterior probabilities . in probcons , posterior probabilities are derived using an hmm whose parameters that have been estimated via supervised learning on balibase unaligned sequences .
probalign , which is largely based on the probcons scheme , derives the posterior probabilities from the input data by implicitly examining suboptimal ( sum - of - pair ) alignments using the partition function methodology for alignments ( see ( 7 ) for a full description of the algorithm ) .
probalign alignments have been shown to have a statistically significant improvement over probcons , mafft ( 8) and muscle ( 9 ) on all three alignment benchmarks introduced above ( 7 ) .
we present here eprobalign , a web server that automatically computes probalign alignments ; eprobalign also provides a convenient platform to visualize the alignment , generate images , and manipulate the output by average column posterior probabilities . the average column posterior probability ( which is discussed further below )
can be considered a measure of column reliability where columns with higher scores are more likely to be correct and perhaps biologically informative .
eprobalign checks the dataset to make sure it conforms with iupac nucleotide and amino acid one letter abbreviations .
white space between residues / nucleotides in the sequences are stripped and the cleaned sequences are passed on to the queuing system .
the user can specify gap open , gap extension , and thermodynamic temperature parameters on the eprobalign input page ( figure 1 ) .
the input page provides a brief description of the parameters ( help link ) and links to the standalone probalign code with publication and datasets . 

the three probalign parameters on the input page are used for computing the partition function dynamic programming matrices from which the posterior probabilities are derived .
this is the same as computing a set of ( suboptimal ) pairwise alignments ( for every pair of sequences in the input ) and then estimating pairwise posterior probabilities by simple counting .
for example , all possible suboptimal alignments would be considered at infinite temperature , whereas only the single best would be used at a temperature of zero .
subsequently , probalign computes the maximal expected accuracy alignment from the posterior probabilities in the same way that probcons does ( 6 ) .
the eprobalign output provides three options for viewing and analyzing the alignment ( figure 2 ) .
the alignment can be viewed in ( i ) fasta text format , ( ii ) pdf graphical format , and ( iii ) the probalign alignment viewer ( pav ) applet ( figure 4 ) .
each column of the alignment in the pdf file and in the applet is colored in a shade of red according to the average column posterior probability .
bright red indicates probability close to one whereas white indicates close to zero ( see figure 4 for an example on a real balibase dataset ) . 

the average column posterior probability is defined as the sum of posterior probabilities of all pairwise residues in the column normalized by the number of comparisons ( 6 ) .
the top row of the alignment in the pdf and applet displays the average column posterior probabilities multiplied by ten and floored to the lower integer ( figure 4 ) .
for example , a score of 1 indicates that the probability is between 0.1 and 0.2 .
the probalign alignment viewer is a java applet that provides basic manipulation of the alignment .
basic java and browser requirements to use the applet are listed on the output page . with the applet
the user can opt to view and save the alignment with column posterior probabilities above any specified threshold .
this has the benefit of  cleaning up  the alignment by column posterior probabilities , which is unique to eprobalign .
the applet also displays posterior probabilities of all columns in a separate window if desired ( figure 3 ) and provides options to switch between the gapped and ungapped versions of the alignment . 
 figure 3.posterior probability of each column . 

we implement a first - in / first - out queuing system that receives requests for probalign alignments and processes them accordingly . at most
, eprobalign will run two probalign jobs at once , and it will periodically check the queue for new requests .
alignments that take longer than some defined time limit ( 10 hours at the time of writing of this paper ) are stopped and the user is advised to download and run the standalone version .
currently , eprobalign is installed on a dual processor 2.8ghz intel xeon machine with 2 gb ram . with these settings
we have also tested large datasets ( in number and length of sequences ) from balibase rv30 and rv40 classes on eprobalign .
bb30029 and bb30008 from rv30 contain 98 and 36 sequences with lengths from 431 to 852 and 400 to 1155 respectively , and bb40002 from rv40 contains 55 sequences with lengths ranging from 58 to 1502 . when the server is idle , eprobalign finished in about 20 minutes on bb30008 , 55 minutes on bb30029 , and 30 minutes on bb40002 .
results may take longer to finish when the server queue is full and multiple jobs are running simultaneously .
however , the effect of parallel jobs will diminish as the server moves to a bigger machine in the near future .
 probalign computes maximal expected accuracy multiple sequence alignments from partition function posterior probabilities . to date , probalign is among the very best scoring methods on the balibase , homstrad and oxbench benchmarks . here 
 , we introduce eprobalign , which is an online implementation of the approach . moreover , the eprobalign web server doubles as an online platform for post - alignment analysis . the heart - and - soul of the post - alignment functionality is the probalign alignment viewer applet , which provides users a convenient means to manipulate the alignments by posterior probabilities . 
 the viewer can also be used to produce graphical and text versions of the output . 
 the eprobalign web server and underlying probalign source code is freely accessible at http://probalign.njit.edu 
INTRODUCTION
INPUT PARAMETERS
OUTPUT AND ALIGNMENT COLUMN RELIABILITY
SERVER IMPLEMENTATION
SCALABILITY