REAL WORLD APPLICATION OF ALGORITHM
Algorithms can be pictured with familiar symbols (see link) like boxes,
diamond shapes, circles, etc. connected by arrows showing various points of
decision making, and what conclusions can be drawn if you end up at a given
point (presuming you followed the 'flow' correctly, and answered the questions
accurately-- and also presuming that the algorithm is rigorous.)
Of course, the concept is easily applicable to all kinds of engineering and theoretical areas. Algorithms are 'heuristic', meaning that they are seen as basically unjustified, and incapable of justification in and of themselves. This is really a basic and very powerful idea. Heuristics are completely flexible, and they can grow and change as the various conclusions and outcomes are examined.
A real world example
Researchers at the Stanford University School of Medicine have used an innovative mathematical technique to find markers that effectively predict how deadly a cancer will be. The discovery, which in this case concerned bladder cancer, could lead to faster, less expensive and more accurate analysis of cancer risk and better treatment of the disease.
The findings were published online Jan. 16 in the Proceedings of the National Academy of Sciences. This is the first study in which a special Stanford-designed computer algorithm was used to identify a clinically prognostic marker from public databases, though the search tool was introduced in a paper published two years ago that established its effectiveness in identifying markers in mice.
Bladder cancer is the sixth most common malignancy and is responsible for about 15,000 deaths per year in the United States. Currently, the severity and aggressiveness of bladder cancer is gauged by a pathologist who inspects a sample of the cancer tissue in the laboratory. This approach requires time and the expertise of a pathologist with special training. “This approach is very subjective and can result in conflicting reports from expert pathologists,” The new research offers the promise of an easy, antibody-based test that can be used by someone with little training to quickly determine whether a bladder cancer is of the most dangerous type.
“This technique might be used to identify the patients with the more-aggressive subtype before the cancer becomes invasive or metastatic.”
To devise this new test, the researchers took an approach, based in developmental biology, to assess the cancer. They started with the knowledge that cancer cells that are more “primitive” (closer in appearance and function to stem cells) are more dangerous than cancer cells that are more “differentiated” (less similar to stem cells). They also knew from previous research that two molecules, keratin-5 and keratin-20, were associated with more-differentiated bladder cells (both normal and cancerous).
cancer cell
The researchers used a unique tool — the computer algorithm developed at Stanford — that allows them to take two biologically related proteins and quickly sort through thousands of public databases to find other molecules that are similarly related. The validity of this “Boolean” search strategy had been demonstrated in a research paper published in 2010 that looked at development of immunological cells in mice. Using this technique, they found another molecule, keratin-14, that was associated with less-differentiated, more-primitive bladder cells
.
With this information in hand, they hypothesized that bladder cancers generally come in three types corresponding to the different forms of keratin, and that the bladder cancer cells making keratin-14 would be the most malignant. The researchers then found cell surface markers unique to each of these types of cells and used antibodies to collect purified cells for further experiment.
The validity of this approach was confirmed when the scientists analyzed pathological samples from former bladder cancer patients and found that the presence of cells creating keratin-14 were indeed associated with worse prognoses. The researchers also used their antibodies to isolate different types of bladder cancer cells and showed that the “primitive” cells associated with keratin-14 could cause the most aggressive cancer when transplanted into mice.
While a bladder cancer test that uses antibody staining will not replace staging and grading by a pathologist, it offers additional information that can lead to more accurate diagnosis. “It also can provide rapid information about the cancer in rural areas or poor countries where a pathologist experienced with bladder cancer may not be immediately available,” said Sahoo, the researcher who developed the Boolean search algorithm.
.
.
what is an algorithm?
an algorithm (the
word is based on the name of the Arabic scholar who developed the concept) is a
finite list of steps that can be taken in order to solve a specific problem or
to produce a certain result. It is important to note that an algorithm does not
put you into an infinite loop. There is a path to a final conclusion. It was
first developed as a set of procedures for doing arithmetic calculations.
Of course, the concept is easily applicable to all kinds of engineering and theoretical areas. Algorithms are 'heuristic', meaning that they are seen as basically unjustified, and incapable of justification in and of themselves. This is really a basic and very powerful idea. Heuristics are completely flexible, and they can grow and change as the various conclusions and outcomes are examined.
A real world example
Stanford designed computer algorithm to predict cancer risk
Researchers at the Stanford University School of Medicine have used an innovative mathematical technique to find markers that effectively predict how deadly a cancer will be. The discovery, which in this case concerned bladder cancer, could lead to faster, less expensive and more accurate analysis of cancer risk and better treatment of the disease.
The findings were published online Jan. 16 in the Proceedings of the National Academy of Sciences. This is the first study in which a special Stanford-designed computer algorithm was used to identify a clinically prognostic marker from public databases, though the search tool was introduced in a paper published two years ago that established its effectiveness in identifying markers in mice.
Bladder cancer is the sixth most common malignancy and is responsible for about 15,000 deaths per year in the United States. Currently, the severity and aggressiveness of bladder cancer is gauged by a pathologist who inspects a sample of the cancer tissue in the laboratory. This approach requires time and the expertise of a pathologist with special training. “This approach is very subjective and can result in conflicting reports from expert pathologists,” The new research offers the promise of an easy, antibody-based test that can be used by someone with little training to quickly determine whether a bladder cancer is of the most dangerous type.
“This technique might be used to identify the patients with the more-aggressive subtype before the cancer becomes invasive or metastatic.”
To devise this new test, the researchers took an approach, based in developmental biology, to assess the cancer. They started with the knowledge that cancer cells that are more “primitive” (closer in appearance and function to stem cells) are more dangerous than cancer cells that are more “differentiated” (less similar to stem cells). They also knew from previous research that two molecules, keratin-5 and keratin-20, were associated with more-differentiated bladder cells (both normal and cancerous).
The researchers used a unique tool — the computer algorithm developed at Stanford — that allows them to take two biologically related proteins and quickly sort through thousands of public databases to find other molecules that are similarly related. The validity of this “Boolean” search strategy had been demonstrated in a research paper published in 2010 that looked at development of immunological cells in mice. Using this technique, they found another molecule, keratin-14, that was associated with less-differentiated, more-primitive bladder cells
.
With this information in hand, they hypothesized that bladder cancers generally come in three types corresponding to the different forms of keratin, and that the bladder cancer cells making keratin-14 would be the most malignant. The researchers then found cell surface markers unique to each of these types of cells and used antibodies to collect purified cells for further experiment.
The validity of this approach was confirmed when the scientists analyzed pathological samples from former bladder cancer patients and found that the presence of cells creating keratin-14 were indeed associated with worse prognoses. The researchers also used their antibodies to isolate different types of bladder cancer cells and showed that the “primitive” cells associated with keratin-14 could cause the most aggressive cancer when transplanted into mice.
While a bladder cancer test that uses antibody staining will not replace staging and grading by a pathologist, it offers additional information that can lead to more accurate diagnosis. “It also can provide rapid information about the cancer in rural areas or poor countries where a pathologist experienced with bladder cancer may not be immediately available,” said Sahoo, the researcher who developed the Boolean search algorithm.
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