Abstract: A system, apparatus and method for monitoring clinical state of a user is disclosed. The method for monitoring clinical state of the user comprises the steps of acquiring clinical information of the user from a set of medical devices and non-clinical information of the user from a database, accumulating, on at least one memory device, said clinical and non-clinical information to form an accumulated dataset, analyzing said accumulated dataset based on any or a combination of a predictive model and a historical data comparison model, wherein said analysis of the accumulated dataset comprises assessment of clinical state of the user based on which longitudinal state of the user is predicted over a defined time interval, and displaying, by a display unit, any or a combination of the analyzed clinical information and the analyzed non-clinical information forming part of the accumulated dataset.

Abstract: A computational method for identifying adhesin and adhesin-like proteins, said method comprising steps of computing the sequence-based attributes of a neural network software wherein the attributes are (i) amino acid frequencies, (ii) multiplet frequency, (iii) dipeptide frequencies, (iv),charge composition, and (v) hydrophobic composition, training the artificial neural Network (ANN) for each of the computed five attributes, and identifying the adhesin and adhesin-like proteins having probability of being an adhesin (Pad) as ?0.51; a computer system for performing the method; and genes and proteins encoding adhesin and adhesin-like proteins.