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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Biological data visualization | 4/5 | https://en.wikipedia.org/wiki/Biological_data_visualization | reference | science, encyclopedia | 2026-05-05T14:01:39.614425+00:00 | kb-cron |
In general, two aspects of the relaxation process are measured: the time taken for the magnetic vector to return to its resting state (also known as T1 or spin–lattice relaxation), and the time taken for the axial spin of the hydrogen protons to return to its resting state (also known as T2 or spin–spin relaxation). To create a T1-weighted image, the MR signal is measured by changing the amount of time between RF pulses (also known as the time to repeat, or TR). To create a T2-weighted image, the MR signal is measured by changing the amount of time between delivering the RF pulse and receiving the RF energy signals from the hydrogen protons (also known as the time to echo, or TE). The dominant signal intensities of T1 image weighting are fluid (black due to low intensity), muscle (grey due to intermediate signal intensity), and fat (white due to high signal intensity). Fat suppression is applied to many T1 weighted sequences to suppress the brightness of the signal created by it. The dominant signal intensities of T2 image weighting are fluid (white), muscle (grey), and fat (white). T2 signals are also often emphasized or suppressed depending on what the goal of the imaging is; notable examples include fat suppression, fluid attenuation, and susceptibility weighting. Also of note are proton density (PD) weighted images, which are generated using a long TR and a short TE. PD is useful for differentiating between fluid, hyaline cartilage and fibrocartilage, which makes it ideal for imaging joints. Outside of joint imaging it has largely been replaced by fluid attenuated inversion recovery (FLAIR), an inversion recovery sequence that removes the signal from cerebrospinal fluid.
== Tomography ==
Computed tomography (CT) and positron emission tomography (PET) scans are similar to MRI, but rely on different imaging techniques (X-rays and ionizing radiation, respectively). A variation of CT known as contrast CT also requires the subject to take in a contrast medium called a radiocontrast (typically by oral consumption, enema, or injection). Positive radiocontrast agents such as barium sulfate increase the body's X-ray attenuation, causing the tissue containing them to appear whiter in the X-ray image. Meanwhile, negative agents such as carbon dioxide gas allow X-rays to pass through them easily, causing the tissues containing them to appear darker. Like magnetic resonance imaging, CT scans use numerous methods to display and measure data, including sequential CT (where the CT table steps from location to location), spiral CT (where the entire X-ray tube is spun around the subject), and electron beam tomography (where only the electron paths are spun using deflection coils). PET scanners don't have quite as much hardware variation and instead use different radiotracers depending on what the imaging target is. Note that radiotracers are distinct from radiocontrasts; the former relies on radioactive decay to trace its path while the latter is absorbed into specific tissue and affects that tissue's X-ray attenuation. Because these methods are not mutually exclusive, PET and CT can be performed simultaneously using PET-CT scanners, which are used for the majority of modern PET scans. Either or both of these methods can be used in conjunction with maximum intensity projection (MIP) to convert the scan data into a 3D image. This can be difficult to accomplish due to artifacts created by respiration and bloodflow, which can appear as abnormalities to an untrained eye; however, it's possible to distinguish these artifacts from real disease so long as careful attention is paid to them. When done well, CT and PET scans taken with MIP are excellent for identifying small abnormal tissue growths, especially in the lungs. Scans taken with MIP for this purpose tend to have higher significance than averaged images created with traditional CT. MIP imaging is also used with magnetic resonance angiography, and research has indicated that it could feasibly be used with MRI. At least one study has shown that MIP MRI actually significantly outperforms single-slice MRI when used by neural networks to classify lesions based on malignancy.
== Alignment == A sequence alignment is a way of arranging the sequences of protein, RNA or DNA, to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. The concept initially compares only two such sequences in the so called pairwise alignment. Global alignments, which attempt to align every residue in every sequence, are most useful when the sequences in the query set are similar and of roughly equal size. Local alignments are more useful for dissimilar sequences that are suspected to contain regions of similarity or similar sequence motifs within their larger sequence context. Multiple sequence alignment is an extension of pairwise alignment to incorporate more than two sequences at a time. Multiple alignment methods try to align all the sequences in each query set. Multiple alignments are often used in identifying conserved sequence regions across a group of sequences hypothesized to be evolutionarily related. Purposes of Alignment Visualization:
Aid general understanding of large-scale DNA or protein alignments. When analyzing data, it is helpful to visualize it somehow, to be able to easily spot clear patters or relations. Visualize alignments for figures and publication. It summarizes the multiple sequence alignment in an easy-to-digest form. Manually edit and curate automatically generated alignments. Even though there are efficient algorithms, none is perfect and visualization tools provide a way to edit small discrepancies.