Median alignment

USAGE SUMMARY

The phrase "Median alignment" is correct and usable in written English.
It can be used in contexts related to design, layout, or data analysis where items or values are arranged in relation to the median. Example: "To ensure a balanced appearance, we need to adjust the median alignment of the text boxes on the page."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

8 human-written examples

We show on lung CT scans that our technique works at near interactive speed and that the median alignment error of 134 nodules is 1.70 mm compared to the error 2.14 mm of the Diffeomorphic Demons algorithm, and to the error 3.57 mm of the global nodule registration with local refinement.

Medical Image Analysis

For the top 100 hits, the median alignment identity increases to 52%.

Bioinformatics

Read mapping resulted in median alignment depths of 20, 20, and 23 for A. merus, A. arabiensis, and A. quadriannulatus, respectively.

G3: Genes, Genomes, Genetics

To model the effects of database bias, the relationships between the number of KO-family members in the database and the median alignment identity of all true positive hits of peptides were plotted.

BMC Genomics

Restricting the analysis to the top 100 significant hits for each query increases the median alignment identity to 53%, which in turn decreases incomplete alignments to 5%, and increases the overextension to 10%.

Bioinformatics

The median total raw reads for the normal and tumor samples were approximately 11.8 million and 16.3 million separately, and the median alignment rates for the normal and tumor samples were 93.01% and 92.48% separately (Supplementary Table 2 and Supplementary Table 3).

BioMed Research International

Human-verified similar examples from authoritative sources

Similar Expressions

52 human-written examples

This was not the case in our study: although the median leg alignment was different, the knees that did not need ligament releases had a leg alignment in preoperative standing radiographs ranging from 11° valgus to 13° varus; the patients were therefore not those with the least deformed legs.

Acta Orthopaedica

The median leg alignment on the preoperative standing radiograph was significantly different for the knees in the 3 release categories (p < 0.001).

Acta Orthopaedica

The release of this structure led to a 4° median change in alignment in extension; the median change in femoral rotation in flexion was 1.5° exorotation.

Acta Orthopaedica

Median preoperative leg alignment on the preoperative standing radiograph was 3° valgus (range 11° valgus to 13° varus) for "no releases", 7° varus (range 0° to 14° varus) for "medial releases", and 4.5° valgus (range 1° valgus to 8° valgus) for "lateral releases" (Table).

Acta Orthopaedica

Only 2 correspond exactly to the breakpoint predicted by the alignments and 20%% were found to be within 6 bp, the median distance to the alignment gap position being 25 bp.

BMC Genomics

Expert writing Tips

Best practice

When describing data distributions, use "median alignment" to specifically indicate that the alignment is based on the median value, rather than the mean or another measure. This ensures clarity and precision, especially in scientific or statistical contexts.

Common error

Avoid using "median alignment" interchangeably with "mean alignment". The median represents the middle value, while the mean is the average. Using the wrong term can misrepresent the data and lead to incorrect interpretations.

Linguistic Context

The phrase "median alignment" functions as a noun phrase, often used as an adjective to describe a specific type of alignment. The term indicates that the alignment process is based on the median value of a set of data points, rather than the mean or average. Ludwig examples showcase usage in scientific contexts.

Expression frequency: Uncommon

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Academia

0%

Ludwig's WRAP-UP

In summary, "median alignment" is a noun phrase used to describe an alignment process based on the median value, primarily in scientific and technical contexts. As indicated by Ludwig, this term highlights a specific statistical method for data arrangement, differing from mean-based approaches. The phrase is grammatically correct and suitable for formal communication, particularly when discussing data analysis or image processing techniques. Using "median alignment" ensures precision, especially when outliers could skew the results if using the mean. Always consider "center alignment" as an alternative if the specific context is visual.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

Center alignment

Focuses on the central positioning of elements, often in a visual or layout context, without necessarily implying a statistical median.

Central alignment

Similar to "center alignment", emphasizing the central location but can also relate to abstract arrangements.

Middle alignment

Specifies positioning in the middle, often referring to vertical alignment in design or layout.

Average alignment

Emphasizes the concept of an average position, which is related to the median but uses a different measure of central tendency.

Mean alignment

Focuses on the arithmetic mean as a measure of central tendency for alignment.

Balanced arrangement

Implies an even distribution or positioning, which can be related to the concept of a median.

Symmetrical alignment

Focuses on mirrored or balanced positioning around a central point, distinct from a median.

Equidistant arrangement

Highlights equal spacing or distance from a central point, differing from median in application.

Normalized alignment

Suggests aligning to a standard or reference point, possibly related to a statistical normalization around the median.

Statistical centering

Highlights the process of centering data around its statistical median for analysis.

FAQs

How is "median alignment" used in image analysis?

In image analysis, "median alignment" often refers to aligning multiple images based on the median pixel intensity or feature location to reduce the impact of outliers or noise. For example, aligning a series of lung CT scans to improve nodule detection.

What does "median alignment" mean in bioinformatics?

In bioinformatics, "median alignment" can refer to aligning sequences of DNA or protein based on the median length or identity score to identify conserved regions or evolutionary relationships. Alternatives include considering a "consensus sequence".

When should I use "median alignment" instead of "average alignment"?

"Median alignment" should be used when the data contains outliers that could skew the average. The median is less sensitive to extreme values, providing a more robust measure of central tendency. In scenarios where outliers are not a concern, "average alignment" may be suitable.

Is "median alignment" a common term in statistics?

While "median" is a fundamental concept in statistics, the specific phrase "median alignment" is more common in applied fields like image processing and bioinformatics where alignment processes are used in conjunction with statistical measures to enhance the accuracy and robustness of analysis.