You will be presented with the full text of a biomedical research paper. Please write an abstract for this paper. Your response should include the abstract and no additional text.

Paper text:
the t cells of the immune system recognize antigens as short peptide fragments ( t - cell epitopes ) derived from self or foreign proteins .
foreign peptides are derived from pathogens , environmental antigens , tumor cells and transplanted tissue .
immune recognition of both self and foreign antigens involves proteolytic processing of antigens , binding of the peptide epitopes by major histocompatibility complex ( mhc ) molecules and presentation of selected peptide epitopes on the cell surface to activate of t cells ( 14 ) .
cytotoxic t cells ( cd8 ) recognize peptides bound to mhc class i molecules and helper t cells ( cd4 ) recognize antigen in the context of mhc class ii molecules .
mhc class i molecules are present in all cells and bind mainly endogenous peptides ( those produced within the presenting cell ) , whereas class ii molecules are present mainly in cells that recognize foreign proteins , such as macrophages and dendritic cells .
t - cell epitopes are critical for the immune response to infectious , autoimmune , allergic and neoplastic disease .
they have been studied for the development of peptide - based vaccines ( 5 ) and may also be important in the diagnosis of pathogens .
it is estimated that between 1 and 5% of all peptides can bind a particular mhc molecule ( 6 ) .
traditional approaches to the identification of t - cell epitopes that involve various biochemical and functional assays of overlapping peptides derived from proteins of interest are costly and not applicable to large - scale studies .
accurate predictions using computer models help speed up the identification of t - cell epitopes ( 7 ) , minimize the number of experiments necessary and enable systematic scanning for candidate t - cell epitopes from larger sets of protein antigens , such as those encoded by complete viral genomes ( 8) .
the balb / c inbred laboratory mouse strain is one of the most commonly used animal models in immunological studies and has been used extensively in vaccine research ( 9,10 ) .
balb / c mice express three class i ( h2-k , h2-l and h2-d ) and two class ii ( i - a and i - e ) molecules . several publicly available prediction systems for mhc class i and class
syfpeithi ( 11 ) has h2-k and h2-l models , bimas ( 12 ) has h2-k , h2-d and h2-l models , and rankpep ( 13 ) has models for all h2 molecules .
these are general servers that contain prediction models for a range of mhc molecules in human and mouse , and several other mammalian organisms , but the accuracies of individual models have not been determined . on the other hand , quantitative matrices for h2-k , h2-d , h2-l and h2-k ( 14,15 ) have been developed and validated .
pred is a computational system for the prediction of peptides binding to all five mhc molecules in balb / c mice ( h2 ) class i ( h2-k , h2-l and h2-d ) and class ii ( i - a and i - e ) that allows analysis of proteins for the presence of binding motifs to all five h2 molecules in parallel .
we derived the initial quantitative matrices for pred using logarithmic equations based on the frequency of amino acids at specific positions within the training set of 9mer peptides as described previously ( 16 ) .
the initial matrices were refined by including information on the consensus ( 11 ) and other binding motifs , for example , h2-k binding peptides that have i , l or m at major anchor position p2 ( 17 ) .
the anchor positions ( e.g. positions 2 and 9 in k binding peptides ) were assigned higher weights than other positions .
in addition , the prediction scores were inspected for all permissible amino acids at each of the anchor positions .
all amino acids at the anchor positions other than the permissible ones were assigned low scores to exclude peptides with non - permissible amino acids from the list of predicted binders .
the final binding scores were normalized to a scale of 19 and the final models were tested and validated rigorously . to our knowledge , pred is the first online server for the prediction of peptides binding to a complete set of mhc molecules in a model organism ( h2 haplotype ) .
the training data containing binding and non - binding peptides were extracted from mhcpep ( 18 ) , mhcbn ( 19 ) , syfpeithi ( 11 ) , jenpep ( 20 ) and a set of non - binders ( v. brusic , unpublished data ) .
the 9mer peptides were used for deriving h2 class i matrices because the majority of peptides that bind these molecules are 9 amino acids long ( 21 ) .
although the majority of h2 class ii binding peptides are 1220 amino acids long , their binding cores are 9 amino acids long ( 22,23 ) .
an iterative elimination method starting from i - a and i - e motifs in syfpeithi ( 11 ) was used to identify the core 9mer regions from long peptides ( k.n .
no one method of predicting peptide  mhc binding consistently outperforms the rest and the most appropriate predictive model depends on the amount of data available in ref .
( 16 ) . in our previous work , an artificial neural network method and hidden markov models
were applied to the prediction of human leukocyte antigens ( hlas ) binding peptides ( 24,25 ) , where more training data were available .
because relatively small training data sets are available for h2 , we adopted matrix models as the prediction method .
five 9  20 matrices were built , one for each of the five h2 alleles , and 10-fold cross - validations were performed to test the accuracy of the prediction models .
the results show that pred predicts peptides binding to i - e , i - a and h2-k with excellent accuracy [ area under the receiver operating characteristic ( roc ) curve , aroc  0.90 ] , and to h2-d and h2-l with good accuracy ( aroc  0.85 ) .
the models were also rigorously tested using experimentally known peptides from viral , prokaryotic and eukaryotic origins ( 14,2629 ) and validated by in vivo studies using severe acute respiratory syndrome ( sars ) nucleocapsid and hiv gag proteins .
the h2 models accurately predicted 11 out of 12 elispot positive regions from balb / c mice splenocytes immunized with sars nucleocapsid dna vaccines ( data not shown ) .
users have the option to predict peptides binding to all h2 molecules , h2 class i molecules , h2 class ii molecules or a single h2 molecule .
the default selection on the webpage is  all h2 molecules . to perform predictions using pred ,
the user must paste a protein sequence into a textbox and assign a name to the sequence .
if the prediction is run with an input sequence containing symbols other than the 20 amino acid codes ( spaces and carriage returns are allowed ) or the total sequence length is outside the 92000 amino acids range , an error message will be displayed .
the input can be either a contiguous protein sequence or a list of peptides , one per line .
protein sequence ( figure 1a ) , which means the input sequence is treated as a contiguous protein sequence ( carriage returns and line breaks will be ignored ) .
the pred input processing program decomposes protein sequence ( or the list of peptides ) into a series of 9mer peptides overlapping by eight amino acids .
individual 9mer peptides are then submitted for prediction . predicted binding scores for all 9mers are displayed in the result tables ( figure 1b ) .
the 9mer binding scores are within the range 010 ; the higher the score , the higher the probability of the peptide being a binder .
pred has the option to plot the binding scores of all the overlapping 9mer peptides as a graph , in which the x - axis represents the start position of a 9mer peptide and the y - axis represents the binding score of the 9mer peptide ( figure 1c ) .
the user can sort the peptides by their binding scores and choose to view only predicted binders with binding scores above a certain threshold . to assess prediction accuracy
, we used measures of sensitivity se = tp/(tp + fn ) and specificity sp = tn/(tn + fp ) ( tp : true positives ; tn : true negatives ; fp : false positives ; fn : false negatives ) .
the higher the value of sp , the lower is the value of se , which results in lower number of both tps and fps .
the lower the value of sp , the higher is the value of se , which results in higher number of both tps and fps .
raw binding scores are mapped to a linear scale that corresponds to sp values , and therefore the prediction thresholds across different models have similar meaning . for example , when a user sets the threshold to 8 , the specificity of the predictions to all five alleles is 0.8 .
the corresponding sensitivities of each model can be viewed at . when users select the input sequence type to be  a list of peptide sequences , the input sequences separated by carriage returns or line breaks are treated as different peptides ( figure 2a ) .
all overlapping 9mers in each peptide are submitted for prediction . in the result tables , predicted binding scores are represented by the highest individual 9mer binding score within the input peptide .
the predicted binding scores of individual 9mers in each peptide in the list are not shown ( figure 2b ) . to display the top - scoring 9mer peptides from each input peptide ,
the user can use the function  view binding peptides at threshold 9 ( figure 2b ) . in the result page ( figure 2c ) , the 9mers with binding scores equal to or above the threshold of 9
the predicted 9mers are displayed with the names of the h2 alleles to which the 9mer binding scores are above the threshold . for example , the first input peptide , ypilpeylqcvk , has binding scores 9.10 , 7.00 , 5.74 , 7.62 and 8.62 to h2-d , h2-k , h2-l , i - a and i - e , respectively ( figure 2b ) . at threshold 9 ( sp level 0.9 ) , there are no 9mer binders to h2 class ii alleles and the 9mer ilpeylqcv has the highest binding score to h2-d , 9.10 .
thus , in figure 2c , this 9mer is aligned with the input peptide and followed by  d.
pred marks a new direction in predictive modeling of mhc - binding peptides and t - cell epitopes .
the main advantage is that pred focuses on a complete organism and its predictions represent a complete set of predicted targets of t - cell immune responses .
the focus on the complete set of mhc alleles is closer to studies involving laboratory animals .
the balb / c mouse is an important laboratory model and pred is , therefore , useful for the analysis of immunization regimens and deciphering responses to infections .
further development of pred will include addition of matrices for prediction of 8mer and 10mer binders to h2 class i molecules and further improvement of prediction matrices by cyclical refinement  using newly defined binders and non - binders from experiments .
an example of the output pages of pred when the input is a single protein .
the input protein sequence is staphylococcal nuclease ( nase ) , the sequence type chosen is 
the input sequence is decomposed into overlapping 9mers for the prediction of binding scores to each allele .
( c ) graphical view of the predicted binding scores to the i - e molecule .
an example of the output pages of pred when the input is a list of peptides .
the input is a list of peptides from chicken ovalbumin and the h2 alleles of interest are all h2 alleles .
( b ) the main result page . all 9mers in each peptide are submitted for prediction .
the predicted binding scores are represented by the highest individual 9mer binding score of each input peptide .
( c ) the alignment view of the predicted binding peptides at threshold 9 , which indicates that the specificity of the prediction is 0.9 .
predbalb / c is a computational system that predicts peptides binding to the major histocompatibility complex-2 ( h2d ) of the balb / c mouse , an important laboratory model organism . 
 the predictions include the complete set of h2d class i ( h2-kd , h2-ld and h2-dd ) and class ii ( i - ed and i - ad ) molecules . 
 the prediction system utilizes quantitative matrices , which were rigorously validated using experimentally determined binders and non - binders and also by in vivo studies using viral proteins . 
 the prediction performance of predbalb / c is of very high accuracy . to our knowledge , this is the first online server for the prediction of peptides binding to a complete set of major histocompatibility complex molecules in a model organism ( h2d haplotype ) . 
 predbalb / c is available at .