Inferring Relatedness of a Macromolecule to a Sequence Database Without Sequencing

Derivation of biological information of a macromolecule isolate based on sequence similarity is playing a significant role in numerous areas of biological research. However, it is often the case that a researcher obtains more macromolecule isolates than can be sequenced practically, due either to the high cost of sequencing or lack of specialized equipment and personnel. To overcome this difficulty, we study the problem of obtaining biological information (such as sequence information) about a macromolecule isolate using only (i) the fragmentation pattern of that isolate obtained from digestion with enzymes and (ii) a database D of sequences. We investigate a three phase approach to solving this problem. In the first phase, we obtain a restriction pattern of the isolate while analytically deriving the corresponding restriction maps of the sequences in the database. In the second phase, we identify a set S ` D of sequences which have restriction maps that are most similar to the unknown..