Algorithms for sequence analysis via mutagenesis.

Motivation: Despite many successes of conventional DNA sequencing methods, some DNAs remain difficult or impossible to sequence. Unsequenceable regions occur in the genomes of many biologically important organisms, including the human genome. Such regions range in length from tens to millions of bases, and may contain valuable information such as the sequences of important genes.

Unlocking hidden genomic sequence.

Despite the success of conventional Sanger sequencing, significant regions of many genomes still present major obstacles to sequencing. Here we propose a novel approach with the potential to alleviate a wide range of sequencing difficulties. The technique involves extracting target DNA sequence from variants generated by introduction of random mutations.

Proteomic analysis of chronic lymphocytic leukemia subtypes with mutated or unmutated Ig V(H) genes.

Chronic lymphocytic leukemia (CLL) is a common hematopoietic malignant disease with variable outcome. CLL has been divided into distinct groups based on whether somatic hypermutation has occurred in the variable region of the immunoglobulin heavy-chain locus or alternatively if the cells express higher levels of the CD38 protein. We have analyzed the proteome of 12 cases of CLL (six mutated (M-CLL) and six unmutated (UM-CLL) immunoglobulin heavy-chain loci; seven CD38-negative and five CD38-positive) using two-dimensional electrophoresis and mass spectrometry.

A simulated annealing algorithm for finding consensus sequences.

Motivation: A consensus sequence for a family of related sequences is, as the name suggests, a sequence that captures the features common to most members of the family. Consensus sequences are important in various DNA sequencing applications and are a convenient way to characterize a family of molecules.

Results: This paper describes a new algorithm for finding a consensus sequence, using the popular optimization method known as simulated annealing.