Niina Haiminen  Niina Haiminen photo       

contact information

Research Scientist: Computational Biology
T. J. Watson Research Center, Yorktown Heights, NY USA



Linear time algorithms to construct populations fitting multiple constraint distributions at genomic scales
E. Siragusa, N. Haiminen, F. Utro, L. Parida
IEEE/ACM Transactions on Computational Biology and Bioinformatics PP(99), 2017

Host phenotype prediction from differentially abundant microbes using RoDEO
Anna Paola Carrieri, Niina Haiminen, Laxmi Parida
Proc. 13th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics. LNCS (to appear), Springer, 2017


Design of the MCAW compute service for food safety bioinformatics
S. B. Edlund, K. L. Beck, N. Haiminen, L. P. Parida, D. B. Storey, B. C. Weimer, J. H. Kaufman, D. D. Chambliss
IBM Journal of Research and Development 60(5/6), 2016

Scalable Algorithms at Genomic Resolution to fit LD Distributions
Laxmi Parida and Niina Haiminen
In Proc. ACM BCB, Seattle, WA, 2016


SimBA: Simulation Algorithm to Fit Extant-Population Distributions
Laxmi Parida and Niina Haiminen
BMC Bioinformatics 16(82), 2015

Host Trait Prediction of Metagenomic Data for Topology-based Visualization
L. Parida, N. Haiminen, D. Haws, J. Suchodolski
Lecture Notes in Computer Science 8956, 134-149 , Springer, 2015


Comparative exomics of Phalaris cultivars under salt stress
N. Haiminen, M. Klaas, Z. Zhou, F. Utro, P. Cormican, T. Didion, C. Sig Jensen, C.E. Mason, S. Barth, L. Parida
BMC Genomics 15(Suppl 6), S18, BioMed Central Ltd, 2014

BAC Sequencing Using Pooled Methods
CA Saski, FA Feltus, L Parida, and N Haiminen
Bacterial Artificial Chromosomes, in Methods in Molecular Biology 1227(3), Springer, 2014

Best-Fit in Linear Time for Non-generative Population Simulation
Niina Haiminen, Claude Lebreton, Laxmi Parida
Algorithms in Bioinformatics, in Lecture Notes in Computer Science 8701, 247-262, Springer, 2014


Efficient in silico Chromosomal Representation of Populations via Indexing Ancestral Genomes
N. Haiminen, F. Utro, C. Lebreton, P. Flament, Z. Karaman, L. Parida
Algorithms 6(3), 430--441, 2013

The genome sequence of the most widely cultivated cacao type and its use to identify candidate genes regulating pod color
J.C. Motamayor, K. Mockaitis, J. Schmutz, N. Haiminen, D. Livingstone, O.E. Cornejo, S. Findley, P. Zheng, F. Utro, S. Royaert, C. Saski, J. Jenkins, R. Podicheti, M. Zhao, B. Scheffler, others
Genome Biology 14(6), R53, BioMed Central Ltd, 2013

iXora: Exact haplotype inferencing and trait association
F. Utro, N. Haiminen, D. Livingstone, O.E. Cornejo, S. Royaert, R. Schnell, J.C. Motamayor, D.N. Kuhn, L. Parida
BMC Genetics 14(1), 48, BioMed Central Ltd, 2013


GenomicTools: an open source platform for developing high-throughput analytics in genomics
A Tsirigos, N Haiminen, E Bilal, F Utro
In Open source software in life science research: Practical solutions to common challenges in the pharmaceutical industry and beyond, Woodhear Publishing, 2012

Discovering Patterns in Gene Order
Laxmi Parida, Niina Haiminen
Evolutionary Genomics, in Methods in Molecular Biology 855(3), 431-455, Springer, 2012

GenomicTools: a computational platform for developing high-throughput analytics in genomics
Aristotelis Tsirigos, Niina Haiminen, Erhan Bilal, Filippo Utro
Bioinformatics 28(2), 282-283, 2012


Randomization techniques for assessing the significance of gene periodicity results
A Kallio, N Vuokko, M Ojala, N Haiminen, H Mannila
BMC Bioinformatics 12(330), 330, BioMed Central Ltd, 2011

Assessing Pooled BAC and Whole Genome Shotgun Strategies for Assembly of Complex Genomes
Niina Haiminen, F Alex Feltus, Laxmi Parida
BMC Genomics 12(194), 194, BioMed Central Ltd, 2011

Sequencing of a QTL-rich Region of the Theobroma cacao Genome using Pooled BACs and the Identification of Trait Specific Candidate Genes
F A Feltus, C A Saski, K Mockaitis, N Haiminen, L Parida, Z Smith, J Ford, M E Staton, S P Ficklin, B P Blackmon, C-H Cheng, R J Schnell, D N Kuhn, J-C Motamayor
BMC Genomics 12(379), 379, BioMed Central Ltd, 2011


Detecting novel genes with sparse arrays
Arvas, N Haiminen, Smit, Rautio, Vitikainen, Wiebe, Martinez, Chee, Kunkel, Sanche, Nelson, Pakula, Saloheimo, Penttila, Kivioja
Gene 467(1-2), 41--51, Elsevier, 2010

Evaluation of BIC and cross validation for model selection on sequence segmentations
N Haiminen, H Mannila
International Journal of Data Mining and Bioinformatics 4(6), 675--700, Inderscience, 2010


Randomization methods for assessing data analysis results on real-valued matrices
M Ojala, N Vuokko, A Kallio, N Haiminen, H Mannila
Statistical Analysis and Data Mining 2(4), 209-230, Wiley Online Library, 2009


Randomization of real-valued matrices for assessing the significance of data mining results
Markus Ojala, Niko Vuokko, Aleksi Kallio, Niina Haiminen, Heikki Mannila
Proc. SIAM Conference on Data Mining, pp. 494-505, 2008

Algorithms for unimodal segmentation with applications to unimodality detection
N Haiminen, A Gionis, K Laasonen
Knowledge and Information Systems 14(1), 39--57, Springer, 2008

Determining significance of pairwise co-occurrences of events in bursty sequences
N Haiminen, H Mannila, E Terzi
BMC bioinformatics 9(1), 336, BioMed Central Ltd, 2008


Discovering isochores by least-squares optimal segmentation
N Haiminen, H Mannila
Gene 394(1-2), 53--60, Elsevier, 2007

Comparing segmentations by applying randomization techniques
N Haiminen, H Mannila, E Terzi
BMC bioinformatics 8(1), 171, BioMed Central Ltd, 2007


Segmentation and dimensionality reduction
E Bingham, A Gionis, N Haiminen, H Hiisila
Proc. SIAM Conference on Data Mining, pp. 372--383, 2006


Discovering Recurrent Sources in Genomic Sequences
N Haiminen
MSc Thesis, Helsingin yliopisto, 2004

Unimodal segmentation of sequences
N Haiminen, A Gionis
Proc. IEEE Conference on Data Mining, pp. 106--113, 2004