Two-dimensional electrophoresis is a major separating technique for proteins in proteomics. Alignment of gel images is critical for intra-laboratory or even more difficult inter-laboratory gel comparisons. In the paper, we propose a novel iterative closest point (ICP) method for 2D-gel electrophoresis image alignment. The paper seeks to introduce an information theoretic measure as one part of distance metric to gel image alignment. We combine intensity information of spots with geometric information of landmarks by applying information potential idea. The proposed method has been applied to both synthetic and real gel images accessible in public 2D-electrophoresis gel protein databases. The high accuracy and robustness of the algorithm indicate that it is promising for gel image alignment. (c) 2007 Elsevier Inc. All rights reserved.