  The Standard Model of particle physics explains (almost) all observed
non-gravitational microscopic phenomena but has many open theoretical
questions. We are on the threshold of unraveling the mysteries of the Standard
Model and discovering its extension. This could be achieved in the near future
with the help of many experiments in particle physics and cosmology, the LHC in
particular. Assuming that data confirming the existence of new physics beyond
the Standard Model is obtained, one is left with the very important and
challenging task of solving the "Inverse Problem", \emph{viz.} "How can one
deduce the nature of the underlying (perhaps microscopic) theory from data?"
This thesis explores this question in detail, and also proposes an approach to
address the problem in a meaningful way which could prove crucial to the
possible solution to this problem in the future. The proposed approach has
three aspects - a) To systematically study classes of microscopic (string/$M$
theory) constructions to the extent that they could be connected to low energy
physics (electroweak scale), b) To find patterns of experimental observables
which are sensitive to the properties of the underlying theoretical
constructions thereby allowing us to distinguish among different constructions,
and c) To try to get insights about the qualitative features of the theoretical
model from data in a bottom-up approach which complements the top-down approach
and strengthens it as well. This thesis studies all the above aspects in
detail. The methods used and results obtained in this thesis will hopefully be
of great importance in solving the Inverse Problem.
