Biomedical subjects

Thomas J Oldfield

Publications and source records attributed to Thomas J Oldfield.

3 recordsLinked to original sources

PubMed2004

A Java applet for multiple linked visualization of protein structure and sequence.

The amount of biological data available from experimental techniques is huge, and rapidly expanding. The ability to make sense of this vast amount of data requires that we make correlations between distinct biological disciplines using visualization techniques to highlight the critical information. This article describes the visualization techniques of dynamic data brushing, view context maintenance, fisheye sequence view, and a magic lens that have been developed to display protein structure and sequence information.

Computational Biology↗

PubMed2003

Automated tracing of electron-density maps of proteins.

The tracing of experimental electron maps in the field of protein crystallography is not a rate-limiting step for structure elucidation, but does represent the process that requires the most expertise and user time. This paper presents a method for automatically tracing the electron-density maps of proteins which can reliably generate a C(alpha) trace for protein maps with data in the resolution range 1.5-4 A. The number of C(alpha) atoms placed and the precision of atom placement depends on the quality of the map, but even with poor maps (FOM approximately 0.5) the algorithm can provide a significant saving in time over conventional methods of interpretation. The interpretation of six experimental maps is presented at different resolutions and levels of phase error; these show that data with an FOM of 0.7 or better can be entirely traced with no user intervention.

Algorithms↗

PubMed2002

High-resolution crystallographic map interpretation.

This article describes a method for rapid interpretation of high-resolution crystallographic electron-density maps. The implemented algorithm searches for fragments of structure found in proteins and links these together to identify uniquely the atomic structure and sequence order of the atoms within a protein. The algorithm uses a two-dimensional sub-graph isomorphism method with a subsequent post-processing step to screen the results to find correct three-dimensional solutions to each search fragment. The final screening of ambiguous solutions found is performed using incomplete difference distance matrices. The algorithm has an intrinsic error-correction technique that is necessary for analysis of experimental data and should be applicable to a number of fields of bioinfomatics.

Algorithms↗