The phrase "query and reference" is a valid and common phrase in written English.
It is used to refer to a request for information (i.e. a question/query) and the answer or source of that information (i.e. the reference). For example: I had to do some research on the topic, so I sent out a query and reference request to a few colleagues.
Hence, the matching pairs between the query and reference image do not appear regular and thus homography estimation fails.
This tab contains a table, which displays the 2D structures of the query and reference fragment pairs and their corresponding HDs.
The input data to DIALIGN is a series of 1-byte characters that represent either DNA or protein strands of query and reference sequences for comparison (cross comparisons between DNA strands and protein strands are never made).
Only protein coding genes were considered for the query and reference.
Ideally, our detection protocol should i) detect individual repeats with near-optimal sensitivity in a few analysis steps, i.e. requiring only a small effort from the user, and ii) not be sensitive to variation in the query and reference alignments used as input.
We conducted similarity searches with tblastx (translating both query and reference database) and blastn (both query and reference database remain nucleotides) with an E-value threshold of 0.001.
Then, the query and references should be clustered at a similarity cutoff greater than 97%.
Indeed, whichever program, query alignment and reference alignment we used, 13 HEAT repeats ( = 14%) and six ARM repeats ( = 10%) amongst the repeats from known structures remained undetected.
Both SOrt-ITEMS and SPHINX algorithms employ BLAST, a relatively robust algorithm, for quantifying the similarity between query sequences and reference database sequences.
Firstly, miRanda carries out sequence alignment of query (miRNA) and reference (3UTR) sequences through dynamic programming local- alignment based on sequence complementarity.
In conclusion, our biological validation experiments showed that AGEP is capable of identifying gene-by-gene contributions to the similarity between query sample and reference database.
