Blast Search
Blast Search - Related Videos
09:41
Blast Quantification Using Hopkinson Pressure Bars
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Cited by 2 •
2016
This protocol details the use of Hopkinson pressure bars to measure reflected blast loading from near-field explosive events. It is capable of interpolating a pressure-time history at any point on a reflective boundary and as such can be used to fully characterize the spatial and temporal variations in loading produced.
01:28
Database Searching
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2026
Effective research begins with the ability to navigate academic databases efficiently. Unlike general web search engines, scholarly databases are designed to index peer-reviewed articles, conference proceedings, and other credible academic publications. Developing a structured search strategy ensures that researchers can identify relevant, high-quality sources with precision. For example, when studying how sleep patterns relate to circadian rhythms in humans, researchers should move beyond...
05:42
Visual Search for Features and Conjunctions
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2023
Source: Laboratory of Jonathan Flombaum—Johns Hopkins University How do people find objects in cluttered visual scenes? Think, for example, of looking for keys on a messy desk, finding the ripest-looking fruit at the grocery store, locating your car when you can’t quite remember where you parked it, or finding an old friend at an airport exit gate. Clearly, an understanding of visual perception is going to play a role in any answers, and more specifically, an understanding of visual attention...
10:51
Evaluating Primary Blast Effects In Vitro
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Cited by 12 •
2017
Understanding how cells are modulated by exposure to shock waves can help identify the mechanisms behind injuries triggered from blast events. This protocol uses custom-built shock tube equipment to apply shock waves at a range of pressures to cell monolayers and to identify the subsequent effects on cell viability.
06:38
Pattern-based Search of Epigenomic Data Using GeNemo
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2017
Unlike DNA sequence data, epigenomic data are not readily subjected to text-based searches. Presented here are the procedures to use an upgraded version of GeNemo, a web-based bioinformatics tool, to conduct pattern-based searches for similarities in epigenomic data comparing available online databases including Encyclopedia of DNA Elements with user's data.
FAQs
The search begins with short words derived from the query sequence rather than comparing every possible position in full detail. BLAST identifies matching or high-scoring word pairs in database entries, then extends promising matches into longer local alignments. This heuristic approach reduces computation while preserving useful regions of similarity for sequence comparison.
The E-value provides a statistical measure for evaluating whether an observed alignment is meaningful. It should not be treated as the only basis for interpretation, because database coverage and alignment quality also affect the result. Researchers therefore consider statistical significance together with the biological context and the strength of the aligned region.
Results depend on the query sequence, the type and coverage of the sequence database, and the quality of the resulting alignment. A database may lack relevant sequences, limiting what the search can reveal. Conversely, a strong match can provide more useful evidence when the aligned region is clear and biologically appropriate for comparison.
A significant local similarity can suggest that a query sequence has a related function, origin, or evolutionary relationship to a database sequence. These conclusions remain potential inferences rather than automatic confirmations. Researchers use the alignment as evidence to guide annotation and experimental design, while evaluating whether database coverage and alignment quality support the interpretation.
A researcher selects a DNA or protein query sequence and compares it with an appropriate sequence database. BLAST divides the query into short words, searches for matching or high-scoring word pairs, extends those matches into local alignments, and reports their statistical significance. The resulting alignments are then reviewed in light of sequence quality and database coverage.
Biologists use the results to annotate genes, identify homologs, compare sequences from different species, verify cloned sequences, and investigate protein function. The findings can also support studies of genome organization. In each case, the search narrows possible biological interpretations and helps researchers decide which observations or hypotheses warrant further experimental investigation.
A cloned DNA sequence can be compared with database entries to determine whether its aligned regions match the expected sequence or related entries. Researchers examine the reported local alignments and their statistical significance rather than relying on a database match alone. This comparison can support sequence verification and reveal similarities relevant to the clone's expected biological identity.