We \u00a0propose \u00a0an \u00a0automatic, \u00a0programmable \u00a0and \u00a0computational \u00a0model \u00a0consisting \u00a0of
biomolecules[1-5] by transforming a base pair into a one-dimensional matrix containing only 0,1, using the
matrix \u00a0length \u00a0as \u00a0the \u00a0sample \u00a0space, \u00a0representing \u00a0the \u00a0event \u00a0The \u00a0sample \u00a0point \u00a0takes \u00a0the \u00a0percentage \u00a0of \u00a0the
sample space as the percentage of the sample space as the probability of the event, and details the probability
calculation \u00a0problem \u00a0into \u00a0the \u00a0model \u00a0of \u00a0the \u00a0molecular \u00a0calculation \u00a0problem. \u00a0After \u00a0the \u00a0introduction \u00a0of \u00a0the
molecular \u00a0matrix \u00a0calculation \u00a0probability \u00a0method, \u00a0the \u00a0examples \u00a0are \u00a0given \u00a0to \u00a0illustrate \u00a0the \u00a0realization \u00a0of \u00a0the
complex event molecular matrix calculation probability. In order to verify the feasibility and complexity of
calculating \u00a0the \u00a0probability \u00a0problem \u00a0of \u00a0the \u00a0molecular \u00a0matrix, \u00a0we \u00a0use \u00a0the \u00a0manual \u00a0calculation \u00a0probability \u00a0to
compare \u00a0with \u00a0the \u00a0results \u00a0of \u00a0the \u00a0DNA \u00a0chain \u00a0to \u00a0predict \u00a0the \u00a0DNA \u00a0secondary \u00a0structure \u00a0and \u00a0its \u00a0interaction
through NUPACK[6] software.
