I am involved in research in bioinformatics, classification and data mining. I am the leader of the classification and data mining research group in the Statistics section.
My full publication info is here
Presently, I am particularly interested in a number of things:
Modern microscopy
enables cell biologist to obtain high resolution 3D images of the
cell nucleus. We are especially interested in the spatial
configuration of sub-nuclear bodies, and the relationship of
configuration to function. This raises new challenges for imaging
and analysis. Some recent work
- McManus, K.J., Stephens, D.A., Adams, N.M., Islam, S. A.,
Freemont, P.S. and Hendzel, M. J., 'The transcriptional regulator CBP has defined spatial associations within interphase nuclei' PLOS Comput. Biol., 2(10), (2006), 1271-1283.
- Shiels, C., Adams, N.M., Stephens, D.A., Islam, S., and
Freemont, P.S., 'Quantitative analysis of cell nuclear organisation' PLOS Comput. Biol., 3(7), (2007), 1161-1168.
- Russell, R.A., Adams, N.M., Stephens, D.A., Batty, E.,
Jensen, K. and Freemont, P.S., 'The stable count thresholding (SCT)
algorithm for segmentation of fluorescence microscopy images',
Biophys. J, 96(8),(2009), 3379-3389.
- Adams, N.M and Freemont, P.S. 'Advances in Nuclear Architecture',
Springer (2010), forthcoming.
This is on-going collaboration
with Paul
Freemont and Dave Stephens.
We have recently been awarded a grant from the BBSRC to continue our
work on the study of nuclear architecture. The project will start in
October. More details to follow.
Advances in data acquisition technology have enabled the continuous
collection of data in a variety of contexts, notably sensor
networks. Such contexts require data analysis algorithms that operate
with a single view of each data item, and the have the capacity to adapt to
changes in the underlying stochastic mechanism. Some recent work
- Pavlidis, N.G., Tasoulis, D.K., Adams, N.M and Hand, D.J., 'lambda-perceptron: an adaptive classifier for data streams', Pattern Recog., 44(1) (2011), 78-96.
- Tasoulis, D.K., Adams, N.M., and Hand, D.J., 'Selective fusion of out-of-sequence measurements', Information Fusion, 11(2), (2010), 183-191.
- Anagnostopoulos, C., Tasoulis, D.K., Adams, N.M. and Hand,
D.J. 'Temporally adaptive estimation of logistic classifiers on data streams'. Adv. Data An. Classif., 3(3) (2009), 243-261.
This work is partially supported by the ALADDIN project.
Classification problems are ubiquitous, and are a good example of the
effectiveness of Statistics in the real world. I am especially
interested in complicated contexts, like credit card fraud detection. Outputs
from the EPSRC ThinkCrime project include
- Hand, D.J., Whitrow, C, Adams, N.M., Juszczak, P. and Weston,
D.J.,
'Performance criteria for plastic card fraud detection tools' J. Oper. Res. Soc., 58, (2008), 956-962.
- Juszczak, P., Adams, N.M., Hand, D.J., Whitrow, C. and Weston, D.J., 'Off-the-peg and bespoke classifiers for fraud detection' Comput. Stat. Data An., 52, (2008), 4521-4532.
- Weston, D.J., Hand, D.J., Adams, N.M., Whitrow, C., and
Juszczak,
P.,
'Plastic card fraud detection using peer group analysis' Adv. Data An. Classif., 2(1), (2008), 45-62.
- Whitrow, C., Hand, D.J., Juszczak, P., Weston, D.J., and
Adams, N.M., 'Transaction aggregation as a strategy for credit card
fraud detection', Data Min. Knowl. Disc., 18(1), (2009), 30-55.
- Tasoulis, D.K., Adams, N.M., Weston, D.J. and Hand, D.J., 'Mining information from plastic card transaction streams', in Compstat 2008, Proceedings in Computational Statistics: 18th Symposium, P. Brito (ed), 2008, 315-322.
Data mining involves various types of analysis on large data
sets. We have been involved in defining the sub-area of "pattern
detection and discovery", concerned with finding small local
structures in large data sets. Some work in this area includes
- Hand, D.J., Adams, N.M., and Bolton, R.J. (eds.), 'Pattern
Detection and Discovery' Proceedings of the ESF Exploratory
Workshop, Lecture Notes in Artificial Intelligence, 2477, (Springer:
Berlin) 2002.
- Hand, D.J., Adams, N.M., and Heard, N.A. (invited) 'Pattern discovery tools for detecting cheating in student coursework' in 'Local Pattern Detection' Lecture notes in Computer Science 3539, Morik, K. Boulicault, J.-F. and Siebes, A. ed(Springer) 2005, 39-50.
- Cohen, P.R., Adams, N.M., and Heeringa, B. 'Voting Experts: an algorithm for segmenting sequences' Intelligent Data Analysis, 11(6), (2007), 607-625.
- Ross,G, Adams, N.M. Tasoulis, D.K. and Hand, D.J., 'Streaming annotation and prediction for regime switching data streams'. In Dongwan Shin (ed). Proceedings of the 24th Annual ACM Symposium on Applied Computing, Vol III, (2009), 1501-1505
And a recent review-type article on data mining:
- Adams, N.M. (invited), 'Perspectives on Data Mining', Int. J Market Res, 52(1) (2010), 183-191.