The phrase "alignment process for" is correct and usable in written English.
It can be used when discussing a procedure or method aimed at achieving alignment in a specific context, such as business, technology, or project management.
Example: "The alignment process for the new software implementation will ensure that all team members are on the same page."
Alternatives: "alignment procedure for" or "alignment strategy for".
We present a novel stylus and phantom that simplify the alignment process for more accurate probe calibration.
It is not necessary to do difficult and complex optical alignment process for ammonia analysis than the case of using out-of-plane (z-axis) type optical detector perpendicular to microfluidic devices.
Compared with Gimbaled Inertial Navigation System (GINS), there are two differences in the compass alignment process for Strapdown INS SINSS) as follows: (1) the input signal is the projected sensor data from body frame to calculated navigation frame, not the sensor data; (2) the output control signal participates in navigation solution rather than driving navigation frame directly.
Figure 4 shows the entire image alignment process for a sample image.
The mean net change in the number of data points following this temporal alignment process for each trip was −8.9; 28,320 trips experienced a net addition, receiving an average of 10±19 data points, 13,986 trips experienced a net reduction, losing an average of 56±198 VMS records; 14,776 trips experienced no adjustment in their temporal frequency.
The so called mappability, or uniqueness of the genomic sequence itself is an important factor in the alignment process for next generation sequence data.
B. Alignment: The pipeline conducts two alignment processes for trimmed reads, one used internally for miRDeep2 [ 13 ] to quantify and predict novel miRNAs and another for all RNA quantification, data visualization and miRNA variant detection, both using the popular alignment tool Bowtie [ 14 ].
Figure 20 Alignment process of two range profiles for the global range alignment algorithm.
In order to overcome this obstacle, Berlin et al. developed the MinHash Alignment Process (MHAP) for efficient overlapping of noisy long reads [31].
We set MI-GRAAL to use graphlet degree vector similarity (GDS) alone, as well as to use GDS coupled with sequence similarity (GDS+SEQ); since it is a randomized algorithm, we repeat each alignment process 15 times for GDS and 15 times for GDS+SEQ, to find alignments of the best topological and biological quality.
We allowed some mismatches in the alignment process to account for sequence divergence between White Leghorn and Red Junglefowl [ 41].
