| Summary: | 碩士 === 國立交通大學 === 應用化學系 === 82 === Bidirectional Associative Memory (BAM) and Holography are two
artificial neural networks that have the characteristic of
granting content addressable memory of bidirectional space.
Using the optimized linear combination of heterogeneous forms
of Lyapunov energy, BAM and holography can be shaped into a so-
called Modified Intraconnection Bidirectional Associative
Memory (MIBAM) network. The network developed in this
laboratory is applied in the analysis of mass spectra of
peptides. The a mino acid sequence is an essential piece of
information in the study of peptide molecules. Since the
invention of Fast Atom Bombardment (FAB) ionization, the
peptide sample can be directly introduced to the mass
spectrometer without a lot of pretreatment. Accordingly, mass
spectrometry has evolved as one of the sequencing techniques.
In this study, the calculated amino acid mass fragments are
input as the encode vector of the MIBAM network to obtain the
weighting matrix of the long term memory. The ne twork then
recalls (deduces) the residue of the peptides sequentially
according to the mass spectra. The MIBAM network developed in
this work proves to handle signals of sparse vector (such as
mass signals in this study) extraordinarily well. Several
known peptides are analyzed to test the feasibility of this
technique. The advantages and limitations are discussed.
Apparently this preliminary work has pointed the right
direction for identification of the primary structure of
peptides using our MIBAM network.
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