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  2. Template modeling score - Wikipedia

    en.wikipedia.org/wiki/Template_modeling_score

    A quantitative study [3] shows that proteins of TM-score = 0.5 have a posterior probability of 37% in the same CATH topology family and of 13% in the same SCOP fold family. The probabilities increase rapidly when TM-score > 0.5. The TM-score is designed to be independent of protein lengths.

  3. I-TASSER - Wikipedia

    en.wikipedia.org/wiki/I-TASSER

    I-TASSER is a template-based method for protein structure and function prediction. [1] The pipeline consists of six consecutive steps: 1, Secondary structure prediction by PSSpred

  4. Global distance test - Wikipedia

    en.wikipedia.org/wiki/Global_distance_test

    The global distance test (GDT), also written as GDT_TS to represent "total score", is a measure of similarity between two protein structures with known amino acid correspondences (e.g. identical amino acid sequences) but different tertiary structures.

  5. Talk:Template modeling score - Wikipedia

    en.wikipedia.org/wiki/Talk:Template_modeling_score

    This article is within the scope of WikiProject Molecular Biology, a collaborative effort to improve the coverage of Molecular Biology on Wikipedia. If you would like to participate, please visit the project page, where you can join the discussion and see a list of open tasks.

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  7. Achenbach System of Empirically Based Assessment - Wikipedia

    en.wikipedia.org/wiki/Achenbach_System_of...

    The ASEBA was created by Thomas Achenbach in 1966 as a response to the Diagnostic and Statistical Manual of Mental Disorders (DSM-I). [3] This first edition of the DSM contained information on only 60 disorders; the only two childhood disorders considered were Adjustment Reaction of Childhood and Schizophrenic Reaction, Childhood Type.

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  9. Traceability matrix - Wikipedia

    en.wikipedia.org/wiki/Traceability_matrix

    In software development, a traceability matrix (TM) [1]: 244 is a document, usually in the form of a table, used to assist in determining the completeness of a relationship by correlating any two baselined documents using a many-to-many relationship comparison.