Sentence examples for biological text from inspiring English sources

In 1999, Wilbur, et. al. [3] compared three NER methods (one rule and dictionary based method and two Naïve Bayes statistical methods) to recognize chemical terms in biological text, and concluded that an integrated method might perform best.

Cohen, Murphy, Qian et al. have explored several different aspects of biological text caption analysis [15], including algorithms for parsing the structure of image captions, and techniques for extracting information relating to subcellular localization by automatically analyzing fluorescence microscope images of cells [16], [17].

We have implemented Textpresso, a biological text search and mining tool.

Winck et al. [ 23] obtained encouraging results by applying a context-based preprocessing to data mining of biological text.

The center has developed a number of text mining systems and resources (55 57) and coordinated community efforts for biological text mining (28, 29).

In addition, the model generates a very large amount of candidates from biological text, and it is a semi-automatic, labor-intensive technique requiring human expert's manual input.

The previous work that has received some attention in recent years is the protein-protein interaction finding tool from biological texts [1], [2], [3].

We saw the need to draw upon resources beyond the interviews and thus reviewed appropriate biological texts so that we could identify robust models for the intended two-semester introductory course sequence.

I took four evolutionary biology books (two texts, two edited volumes), four evolutionary psychology texts (including my own), three text/reference books on human evolution and one biological anthropology text and scanned the subject index of each for "social Darwinism".

To benchmark FIRE-pro's performance, we carried out a comparative study of existing methods (Motif-x [21], TEIRESIAS [19], DiLiMot [20], [25], and SLiMFinder [22]) on five biological datasets (Text S1).

Owing to the large and rapidly growing body of literature in the biological sciences text mining approaches are increasingly important for the extraction and collation of data.