BLAST Algorithm– Critical Review

BLAST algorithm is a self-enabling algorithm for exploring nucleic acid and protein databases. It is an effective tool for comparative analysis between query sequences of various nucleic acids and proteins. This article critically reviews the BLAST algorithm, its heuristic potential, categorization of local or global sequence similarity measures, and improvement recommendations. The subject, course code, course name, and college/university are not mentioned.

Data Structure and Algorithms
BLAST Algorithm– Critical Review
BLAST enables a self-enabling algorithm with the objective of systematically
exploring the nucleic acid and protein databases. It is an effective tool utilized for
undertaking a comparative analysis between the query sequences of various nucleic acids and
proteins. BLAST prototype (i.e. BLAST-P) substantially delineates the variations between
the protein databases and queries in a rational manner. The heuristic potential of BLAST
assists in undertaking quick searches in the protein database (Madden, 2013). The expect-
value identified by BLAST assists in tracking the quantity of protein sequence matches on the
basis of probability. This reciprocally influences user’s confidence in the retrieved sequence
alignment. BLAST tool is capable of executing local alignments while effectively searching
for sequences of limited-similarity. They also possess the capacity of globally aligning the
genomic DNA with the mRNA while undertaking genomic analysis and assembly. The
BLAST algorithm effectively filters the query sequence by utilizing the conventions that are
customized for evaluating the low complexity regions. The filtering process is limited to the
query sequence rather than to the entire database sequences. The nucleic acid sequences and
protein sequences are designated by N and X respectively.
BLAST program effectively removes the redundant and low complexity sequences
due to that its focus increases on exploring the more relevant database hits (Mount, 2004).
BLAST is available at NCBI effectively aligns any DNA sequence with other similar or
dissimilar sequences for their comparative evaluation. BLAST algorithm does not compare
each sequence residue and utilizes small segments with the objective of generating the
alignment seed. The user acquires the privilege to generate a self-defined length of words
from a known query sequence. The reduction in unnecessary comparisons enhances the
alignment pace with the utilization of BLAST algorithm. The segregation of three residues

and enhancement of words magnitude (by the BLAST algorithm) facilitates the process of
their comparative analysis while minimizing the regions that require evaluation. BLAST
algorithm effectively adjusts the alignment while following the T (threshold) value
designated by the end user. The BLAST search mechanism facilitates the word extension
beyond the pre-defined threshold value. The algorithm also utilizes a cut off score for
segregating the alignment above the cut off limit for significantly reinforcing homology
between the sequences. Indeed, after the exploration and tracking of a significant hit, the
BLAST algorithm searches the sequence of interest over the extended alignment segment that
exhibits a greater value than the cut off score (Lobo, 2008). Alignment termination is
performed after the sustained reduction of the alignment score below the threshold score
limit. These BLAST mechanisms could be adjusted further with the objective of enhancing
the sensitivity and pace of the algorithm for the timely acquisition of the desirable sequences.
BLAST categorises local or global sequence similarity measures for effectively
optimizing the alignment between the sequences of interest. The BLAST similarity algorithm
systematically excludes the non-conserved sub-sequences and considers the conserved
sequence regions for calculating the similarity score (Altschul, et al., 1990). The local
similarity approaches that are deployed by the BLAST algorithm utilize cDNA for its
comparison with the semi-sequences genes. The isolated similarity locations are displayed by
distant proteins that require systematic comparison with the cDNA by the BLAST algorithm
(Altschul, et al., 1990). The megaBLAST search algorithm related to nucleotide-nucleotide
exploration is useful in comparatively analysing the sequences between the species of related
origin (Madden, 2013). This algorithm effectively explores direct matches for the 28-bases
and subsequently replicates the matches sequences across the entire alignment. The BLASTN
exploratory algorithm compares the nucleotide-nucleotide pattern between the distantly
located sequences (Madden, 2013). Sequence comparisons between various proteins are

executed by the BLASTP algorithm that also facilitates the pattern of TBLASTN and
BLASTX searches. BLASTX search algorithm executes the nucleotide query across the
protein database through its systematic translation. Alignment patterns characterized by
various BLAST hits are segregated with the utilization of the character “>” along with the
subject sequence name and accession number (Leung, 2017).
BLAST Definition line includes the aligned blocks of sequences that incorporate
localized similarity regions between the subject and query sequences. The arrangement of the
aligned blocks is done in accordance with the descending S values that most of the time
mismatch with their structural pattern across the query DNA molecule. The blocks of
sequences require sorting by running the query ‘Sort’ for the effective segregation of blocks
in the desirable patterns. The recent amendments to BLAST algorithms include the extension
of T score, inclusion of gapped alignments and position oriented score matrix (Altschul, et
al., 1997). The BLAST algorithm is challenged by the USEARCH and UBLAST tools that
claim to acquire elevated scoring local and global sequence alignments (Edgar, 2010). These
algorithms are multiple time faster and sensitive than the original BLAST algorithm in their
potential to extract and analyse the protein sequences. BLAST exhibits the capacity of
integrating with the global alignment algorithm for generating a complete primer-target
alignment in the context of exploring the pattern of mismatched primer-based targets (Ye, et
al., 2012). BLAST execution of various algorithms (including BLASTN, BLASTP,
BLASTX, TBLASTN and TBLASTX) requires the importing of the accession number,
subject sequence, query subrange and subject subrange for comparatively analysing a range
of nucleotide sequences (NCBI, 2017).
Improvement Recommendation
BLAST searches are constrained by their smaller list sizes and because of that the
simultaneous retrieval of the entire significant hits proves to be a big challenge for

bioinformaticians. The search query requires multiple executions with the objective of
acquiring the significant sequence findings at a large scale. This substantiates the requirement
of modifying the BLAST search algorithm while effectively increasing the length of search
queries for obtaining the desirable hits in a single execution. The adjustment in the magnitude
of list size will substantially facilitate the scale and sensitivity of the BLAST sequence
comparisons. BLAST algorithm displays the limited quantity of top alignments of the
sequence segments by default. However, this alignment sequence limit requires adjustment in
a manner to produce the desirable sequences pattern while excluding the unlisted sequences.
However, automation of these alignment patterns is highly recommended and would
substantially improve the sensitivity and specificity of the BLAST algorithm results. The
default word size in the BLAST algorithm substantially constraints the specificity of results.
The systematic scoring of the segment pairs eventually requires the generation of
complete matches in accordance with the predefined pattern and magnitude of the optimized
DNA bases. Therefore, another significant recommendation attributes to the requirement of
automating the length of word size while allowing its user-defined variability in a manner to
elevate the sensitivity of the compared sequences. Resultantly, this change of provision in the
word length will facilitate the exploration of a variety of nucleotide patterns in accordance
with the research requirements. The transformation of proteins word size to various limits
without the requirement of manually adjusting the T-threshold will substantially improve the
accuracy of results and generation of unreliable sequences. Utilization of BLAST algorithm
across a lengthy database warrants the execution of searches in the format of batch queues.
This requires executing a multitude of batch commands for sequentially running the batch
queues one after another for increasing the speed of the database search. The development of
an automated process for saving the database search time (by the BLAST algorithm) would
reduce the requirement of manual execution of batch commands and increase the specificity

and sensitivity of the algorithm for acquiring the desirable nucleotide patterns. BLAST
algorithm also requires modification with the objective of extracting the nucleotide-sequence
homologues at the level of amino acids.

References
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Altschul, S. F., Madden, T. L., Schäffer, A. A., Zhang, J., Zhang, Z., Miller, W., & Lipman,
D. J. (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database
search programs. Nucleic Acids Research, 25(17), 3389–3402.
doi:https://doi.org/10.1093/nar/25.17.3389
Edgar, R. C. (2010). Search and clustering orders of magnitude faster than BLAST.
Bioinformatics, 26(19), 2460-2461. doi:https://doi.org/10.1093/bioinformatics/btq461
Leung, W. (2017). Lab Week 8 – An In-Depth Introduction to NCBI BLAST. Washington:
Washington University. Retrieved from
https://community.gep.wustl.edu/wiki/images/2/28/2011_8b_BLASTrv7_rev.pdf
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Mount, D. W. (2004). Using the Basic Local Alignment Search Tool (BLAST). Sequence
Database Searching for Similar Sequences.
NCBI. (2017). BLAST. Retrieved Dec 03, 2017, from https://blast.ncbi.nlm.nih.gov/Blast.cgi?
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LOC=blasttab&LAST_PAGE=blastn&BLAST_INIT=blast2seq

Ye, J., Coulouris, G., Zaretskaya, I., Cutcutache, I., Rozen, S., & Madden, T. L. (2012).
Primer-BLAST: A tool to design target-specific primers for polymerase chain
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