Diskriminantnyy analiz i struktura belka » książka
Diskriminantnyy analiz i struktura belka
ISBN-13: 9783659669675 / Rosyjski / Miękka / 2014 / 104 str.
Protestirovan novyy metod predskazaniya vtorichnoy struktury belka i otsenena ego tochnost' dlya trekh osnovnykh sostoyaniy, prevyshayushchaya tochnost' mnogikh shiroko ispol'zuemykh metodov. Vyyavleno mnozhestvo fiziko-khimicheskikh i funktsional'nykh parametrov belka, kotorye opredelyayut obrazovanie vtorichnoy struktury i otsenen otnositel'nyy vklad kazhdogo iz parametrov. Pokazano, chto na obrazovanii vtorichnoy struktury sushchestvenno vliyanie kak lokal'nykh, tak i global'nykh svoystv polipeptidnoy tsepi. V membrannykh belkakh s vysokoy stepen'yu tochnosti predskazano obrazovanie trekh naibolee rasprostranennykh tipov vtorichnoy struktury. New method to predict protein secondary structure was developed and tested for three main states, the accuracy of the method is higher then many other existing approaches. Many physical-chemical protein properties influence protein structure prediction, each property was characterized by corresponding parameter and its weight. It was shown that both local and global properties of protein chain influence structure prediction. For membrane proteins structure prediction for three main types was achieved with high accuracy.
Protestirovan novyy metod predskazaniya vtorichnoy struktury belka i otsenena ego tochnost dlya trekh osnovnykh sostoyaniy, prevyshayushchaya tochnost mnogikh shiroko ispolzuemykh metodov. Vyyavleno mnozhestvo fiziko-khimicheskikh i funktsionalnykh parametrov belka, kotorye opredelyayut obrazovanie vtorichnoy struktury i otsenen otnositelnyy vklad kazhdogo iz parametrov. Pokazano, chto na obrazovanii vtorichnoy struktury sushchestvenno vliyanie kak lokalnykh, tak i globalnykh svoystv polipeptidnoy tsepi. V membrannykh belkakh s vysokoy stepenyu tochnosti predskazano obrazovanie trekh naibolee rasprostranennykh tipov vtorichnoy struktury. New method to predict protein secondary structure was developed and tested for three main states, the accuracy of the method is higher then many other existing approaches. Many physical-chemical protein properties influence protein structure prediction, each property was characterized by corresponding parameter and its weight. It was shown that both local and global properties of protein chain influence structure prediction. For membrane proteins structure prediction for three main types was achieved with high accuracy.
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