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Bottom–up and top–down are both strategies of information processing and ordering knowledge, used in a variety of fields including software, humanistic and scientific theories (see systemics), and management and organization. In practice they can be seen as a style of thinking, teaching, or leadership.
Top-down vs bottom-up proteomics. Top-down proteomics is a method of protein identification that either uses an ion trapping mass spectrometer to store an isolated protein ion for mass measurement and tandem mass spectrometry (MS/MS) analysis [1] [2] or other protein purification methods such as two-dimensional gel electrophoresis in conjunction with MS/MS. [3] Top-down proteomics is capable ...
Bottom-up processing is also known as data-driven processing, because it originates with the stimulation of the sensory receptors. [10] Psychologist James Gibson opposed the top-down model and argued that perception is direct, and not subject to hypothesis testing as Gregory proposed.
Top-down and bottom-up design of information ordering; Top-down parsing, a parsing strategy beginning at the highest level of the parse tree Top-down parsing language, an analytic formal grammar to study top-down parsers; Top-down perspective, a camera angle in computer and video games; Top-down shooter, a subgenre of video games
Bottom-up parsing, a computer science strategy; Bottom-up processing, in Pattern recognition (psychology) Bottom-up theories of galaxy formation and evolution; Bottom-up tree automaton, in data structures; Bottom-up integration testing, in software testing; Top-down and bottom-up design, strategies of information processing and knowledge ordering
Top-down parsing eagerly decides what a construct is much earlier, when it has only scanned the leftmost symbol of that construct and has not yet parsed any of its parts. Left corner parsing is a hybrid method that works bottom-up along the left edges of each subtree, and top-down on the rest of the parse tree.
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One example of this is a study by Washburn, Wolters, and Yates in which they used shotgun proteomics on the proteome of a Saccharomyces cerevisiae strain grown to mid-log phase. They were able to detect and identify 1,484 proteins as well as identify proteins rarely seen in proteome analysis, including low-abundance proteins like transcription ...