Biomedical subjects

M Eggert

Publications and source records attributed to M Eggert.

3 recordsLinked to original sources

PubMed1992

Parametric sequence comparisons.

Current algorithms can find optimal alignments of two nucleic acid or protein sequences, often by using dynamic programming. While the choice of algorithm penalty parameters greatly influences the quality of the resulting alignments, this choice has been done in an ad hoc manner. In this work, we present an algorithm to efficiently find the optimal alignments for all choices of the penalty parameters. It is then possible to systematically explore these alignments for those with the most biological or statistical interest. Several examples illustrate the method.

Algorithms↗

PubMed1991

Identification of phosphorylation sites on murine nuclear lamin C by RP-HPLC and microsequencing.

Isolated interphase lamin C, obtained from Ehrlich ascites tumor cells, was digested by Lys-C endoproteinase, the resulting peptides separated by reversed-phase HPLC and subjected to microsequencing in order to identify phosphorylation sites in interphase and following phosphorylation in vitro by cdc2-kinase, protein kinase C (PKC) and protein kinase A (PKA), respectively. Nuclear lamin C showed partial phosphorylation of Ser392 and Ser409, and possibly Ser407 in interphase. Phosphorylation was increased in response to cdc2-kinase at Ser390 and Ser392 and to PKC at Ser572. The N-terminal peptide (aa 1-32) containing consensus sequences for the 3 kinases was phosphorylated by cdc2-kinase, PKC and PKA. The sequence data suggests that multiple molecular switches via lamina modification control the dynamic behaviour of the nucleoskeleton during the cell cycle.

Amino Acid Sequence↗

PubMed1987

A new algorithm for best subsequence alignments with application to tRNA-rRNA comparisons.

The algorithm of Smith & Waterman for identification of maximally similar subsequences is extended to allow identification of all non-intersecting similar subsequences with similarity score at or above some preset level. The resulting alignments are found in order of score, with the highest scoring alignment first. In the case of single gaps or multiple gaps weighted linear with gap length, the algorithm is extremely efficient, taking very little time beyond that of the initial calculation of the matrix. The algorithm is applied to comparisons of tRNA-rRNA sequences from Escherichia coli. A statistical analysis is important for proper evaluation of the results, which differ substantially from the results of an earlier analysis of the same sequences by Bloch and colleagues.

Algorithms↗