Computational Biology

In the Genomic Signal Processing Lab at the University of Utah, we develop generalizations of the matrix and tensor computations that underlie theoretical physics, and use them to create models that compare and integrate different types of large-scale molecular biological data, such as DNA microarray data, and computationally predict global mechanisms that govern the activity of DNA and RNA. We believe that future discovery and control in biology and medicine will come from the mathematical modeling of such large-scale molecular biological data data, just as Kepler discovered the laws of planetary motion by using mathematics to describe trends in astronomical data. We pioneered the use of the matrix singular value decomposition (SVD), the tensor higher-order SVD (HOSVD) and their generalizations in modeling different types of genomic data from different studies of cell division and cancer and from different organisms. Our recent experimental results verify our computational prediction of a mechanism of regulation that correlates DNA replication origin activity with mRNA expression, demonstrating for the first time that mathematical modeling of DNA microarray data, in which the mathematical variables and operations represent biological reality, can be used, beyond classification of genes and cellular samples, to correctly predict previously unknown global biological mechanisms. We now extend our recent computational results, modeling data from the Cancer Genome Atlas, to formulate and implement a protocol for the utilization of recent global profiling biotechnologies in the computational prognosis of cancers. Ultimately, our work will bring physicians a step closer to one day being able to predict and control the progression of cancers as readily as NASA engineers plot the trajectories of spacecraft today.

Genomic Signal Processing Lab

Computational Biology

Atrial fibrillation ablation outcome is predicted by left atrial remodeling on MRI
C. McGann, N. Akoum, A. Patel, E. Kholmovski, P. Revelo, K. Damal, B. Wilson, J. Cates, A. Harrison, R. Ranjan, N.S. Burgon, T. Greene, D. Kim, E.V. Dibella, D. Parker, R.S. MacLeod, N.F. Marrouche. In Circ Arrhythm Electrophysiol, Vol. 7, No. 1, pp. 23--30. 2014.
DOI: 10.1161/CIRCEP.113.000689
PubMed ID: 24363354

Although catheter ablation therapy for atrial fibrillation (AF) is becoming more common, results vary widely, and patient selection criteria remain poorly defined. We hypothesized that late gadolinium enhancement MRI (LGE-MRI) can identify left atrial (LA) wall structural remodeling (SRM) and stratify patients who are likely or not to benefit from ablation therapy.

LGE-MRI was performed on 426 consecutive patients with AF without contraindications to MRI before undergoing their first ablation procedure and on 21 non-AF control subjects. Patients were categorized by SRM stage (I-IV) based on the percentage of LA wall enhancement for correlation with procedure outcomes. Histological validation of SRM was performed comparing LGE-MRI with surgical biopsy. A total of 386 patients (91%) with adequate LGE-MRI scans were included in the study. After ablation, 123 patients (31.9%) experienced recurrent atrial arrhythmias during the 1-year follow-up. Recurrent arrhythmias (failed ablations) occurred at higher SRM stages with 28 of 133 (21.0%) in stage I, 40 of 140 (29.3%) in stage II, 24 of 71 (33.8%) in stage III, and 30 of 42 (71.4%) in stage IV. In multivariate analysis, ablation outcome was best predicted by advanced SRM stage (hazard ratio, 4.89; P

Comparison of Left Atrial Area Marked Ablated in Electroanatomical Maps with Scar in MRI
B.R. Parmar, T.R. Jarrett, N.S. Burgon, E.G. Kholmovski, N.W. Akoum, N. Hu, R.S. Macleod, N.F. Marrouche, R. Ranjan. In Journal of Cardiovascular Electrophysiology, 2014.
DOI: 10.1111/jce.12357


Three-dimensional electroanatomic mapping (EAM) is routinely used to mark ablated areas during radiofrequency ablation. We hypothesized that, in atrial fibrillation (AF) ablation, EAM overestimates scar formation in the left atrium (LA) when compared to the scar seen on late-gadolinium enhancement magnetic resonance imaging (LGE-MRI).

Methods and Results

Of the 235 patients who underwent initial ablation for AF at our institution between August 2011 and December 2012, we retrospectively identified 70 patients who had preprocedural magnetic resonance angiography merged with LA anatomy in EAM software and had a 3-month postablation LGE-MRI for assessment of scar. Ablated area was marked intraprocedurally using EAM software and quantified retrospectively. Scarred area was quantified in 3-month postablation LGE-MRI. The mean ablated area in EAM was 30.5 ± 7.5% of the LA endocardial surface and the mean scarred area in LGE-MRI was 13.9 ± 5.9% (P < 0.001). This significant difference in the ablated area marked in the EAM and scar area in the LGE-MRI was present for each of the 3 independent operators. Complete pulmonary vein (PV) encirclement representing electrical isolation was observed in 87.8% of the PVs in EAM as compared to only 37.4% in LGE-MRI (P < 0.001).


In AF ablation, EAM significantly overestimates the resultant scar as assessed with a follow-up LGE-MRI.

Network inefficiencies in autism spectrum disorder at 24 months
J.D. Lewis, A.C. Evans, J.R. Pruett, K. Botteron, L. Zwaigenbaum, A. Estes, G. Gerig, L. Collins, P. Kostopoulos, R. McKinstry, S. Dager, S. Paterson, R. Schultz, M. Styner, H. Hazlett, J. Piven, IBIS network. In Translational Psychiatry, 2014.

Autism Spectrum Disorder (ASD) is a developmental disorder defined by behavioural symptoms that emerge during the first years of life. Associated with these symptoms are differences in the structure of a wide array of brain regions, and in the connectivity between these regions. However, the use of cohorts with large age variability and participants past the generally recognized age of onset of the defining behaviours means that many of the reported abnormalities may be a result of cascade effects of developmentally earlier deviations. This study assessed differences in connectivity in ASD at the age at which the defining behaviours first become clear. The participants were 113 24-month-olds at high risk for ASD, 31 of whom were classified as ASD, and 23 typically developing 24-month-olds at low risk for ASD. Utilizing diffusion data to obtain measures of the length and strength of connections between anatomical regions, we performed an analysis of network efficiency. Our results showed significantly decreased local and global efficiency over temporal, parietal, and occipital lobes in high-risk infants classified as ASD, relative to both low- and high-risk infants not classified as ASD. The frontal lobes showed only a reduction in global efficiency in Broca's area. Additionally, these same regions showed an inverse relation between efficiency and symptom severity across the high-risk infants. The results suggest delay or deficits in infants with ASD in the optimization of both local and global aspects of network structure in regions involved in processing auditory and visual stimuli, language, and nonlinguistic social stimuli.

Noninvasive reconstruction of potentials on endocardial surface from body surface potentials and CT imaging of partial torso
B. Erem, J. Coll-Font, R.M. Orellana, P. Stovicek, D.H. Brooks, R.S. MacLeod. In Journal of Electrocardiology, Vol. 46, No. 4, pp. e28. 2013.
DOI: 10.1016/j.jelectrocard.2013.05.104

Time invariant multi electrode averaging for biomedical signals
R.M. Orellana, B. Erem, D.H. Brooks. In Proceedings of the 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1242--1246. 2013.
ISSN: 1520-6149
DOI: 10.1109/ICASSP.2013.6637849

One of the biggest challenges in averaging ECG or EEG signals is to overcome temporal misalignments and distortions, due to uncertain timing or complex non-stationary dynamics. Standard methods average individual leads over a collection of epochs on a time-sample by time-sample basis, even when multi-electrode signals are available. Here we propose a method that averages multi electrode recordings simultaneously by using spatial patterns and without relying on time or frequency.

Improved averaging of multi-lead ECGs and electrogramsImproved averaging of multi-lead ECGs and electrograms
B. Erem, R.M. Orellana, P. Stovicek, D.H. Brooks, R.S. MacLeod. In Journal of Electrocardiology, Vol. 46, No. 4, pp. e28. 2013.
DOI: 10.1016/j.jelectrocard.2013.05.103

SVD Identifies Transcript Length Distribution Functions from DNA Microarray Data and Reveals Evolutionary Forces Globally Affecting GBM Metabolism
N.M. Bertagnolli, J.A. Drake, J.M. Tennessen, O. Alter. In Public Library of Science (PLoS) One, Vol. 8, No. 11, pp. article e78913. November, 2013.
DOI: 10.1371/journal.pone.0078913

To search for evolutionary forces that might act upon transcript length, we use the singular value decomposition (SVD) to identify the length distribution functions of sets and subsets of human and yeast transcripts from profiles of mRNA abundance levels across gel electrophoresis migration distances that were previously measured by DNA microarrays. We show that the SVD identifies the transcript length distribution functions as “asymmetric generalized coherent states” from the DNA microarray data and with no a-priori assumptions. Comparing subsets of human and yeast transcripts of the same gene ontology annotations, we find that in both disparate eukaryotes, transcripts involved in protein synthesis or mitochondrial metabolism are significantly shorter than typical, and in particular, significantly shorter than those involved in glucose metabolism. Comparing the subsets of human transcripts that are overexpressed in glioblastoma multiforme (GBM) or normal brain tissue samples from The Cancer Genome Atlas, we find that GBM maintains normal brain overexpression of significantly short transcripts, enriched in transcripts that are involved in protein synthesis or mitochondrial metabolism, but suppresses normal overexpression of significantly longer transcripts, enriched in transcripts that are involved in glucose metabolism and brain activity. These global relations among transcript length, cellular metabolism and tumor development suggest a previously unrecognized physical mode for tumor and normal cells to differentially regulate metabolism in a transcript length-dependent manner. The identified distribution functions support a previous hypothesis from mathematical modeling of evolutionary forces that act upon transcript length in the manner of the restoring force of the harmonic oscillator.

Evaluation of Current Algorithms for Segmentation of Scar Tissue from Late Gadolinium Enhancement Cardiovascular Magnetic Resonance of the Left Atrium: An Open-Access Grand Challenge
R. Karim, R.J. Housden, M. Balasubramaniam, Z. Chen, D. Perry, A. Uddin, Y. Al-Beyatti, E. Palkhi, P. Acheampong, S. Obom, A. Hennemuth, Y. Lu, W. Bai, W. Shi, Y. Gao, H.-O. Peitgen, P. Radau, R. Razavi, A. Tannenbaum, D. Rueckert, J. Cates, T. Schaeffter, D. Peters, R.S. MacLeod, K. Rhode. In Journal of Cardiovascular Magnetic Resonance, Vol. 15, No. 105, 2013.
DOI: 10.1186/1532-429X-15-105

Background: Late Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging can be used to visualise regions of fibrosis and scarring in the left atrium (LA) myocardium. This can be important for treatment stratification of patients with atrial fibrillation (AF) and for assessment of treatment after radio frequency catheter ablation (RFCA). In this paper we present a standardised evaluation benchmarking framework for algorithms segmenting fibrosis and scar from LGE CMR images. The algorithms reported are the response to an open challenge that was put to the medical imaging community through an ISBI (IEEE International Symposium on Biomedical Imaging) workshop.

Methods: The image database consisted of 60 multicenter, multivendor LGE CMR image datasets from patients with AF, with 30 images taken before and 30 after RFCA for the treatment of AF. A reference standard for scar and fibrosis was established by merging manual segmentations from three observers. Furthermore, scar was also quantified using 2, 3 and 4 standard deviations (SD) and full-width-at-half-maximum (FWHM) methods. Seven institutions responded to the challenge: Imperial College (IC), Mevis Fraunhofer (MV), Sunnybrook Health Sciences (SY), Harvard/Boston University (HB), Yale School of Medicine (YL), King’s College London (KCL) and Utah CARMA (UTA, UTB). There were 8 different algorithms evaluated in this study.

Results: Some algorithms were able to perform significantly better than SD and FWHM methods in both pre- and post-ablation imaging. Segmentation in pre-ablation images was challenging and good correlation with the reference standard was found in post-ablation images. Overlap scores (out of 100) with the reference standard were as follows: Pre: IC = 37, MV = 22, SY = 17, YL = 48, KCL = 30, UTA = 42, UTB = 45; Post: IC = 76, MV = 85, SY = 73, HB = 76, YL = 84, KCL = 78, UTA = 78, UTB = 72.

Conclusions: The study concludes that currently no algorithm is deemed clearly better than others. There is scope for further algorithmic developments in LA fibrosis and scar quantification from LGE CMR images. Benchmarking of future scar segmentation algorithms is thus important. The proposed benchmarking framework is made available as open-source and new participants can evaluate their algorithms via a web-based interface.

Mechanistic Inquiry into the Role of Tissue Remodeling in Fibrotic Lesions in Human Atrial Fibrillation
K.S. McDowell, F. Vadakkumpadan, R. Blake, J. Blauer, G.t Plank, R.S. MacLeod, N.A. Trayanova. In Biophysical Journal, Vol. 104, pp. 2764--2773. 2013.
DOI: 10.1016/j.bpj.2013.05.025
PubMed ID: 23790385

Atrial fibrillation (AF), the most common arrhythmia in humans, is initiated when triggered activity from the pulmonary veins propagates into atrial tissue and degrades into reentrant activity. Although experimental and clinical findings show a correlation between atrial fibrosis and AF, the causal relationship between the two remains elusive. This study used an array of 3D computational models with different representations of fibrosis based on a patient-specific atrial geometry with accurate fibrotic distribution to determine the mechanisms by which fibrosis underlies the degradation of a pulmonary vein ectopic beat into AF. Fibrotic lesions in models were represented with combinations of: gap junction remodeling; collagen deposition; and myofibroblast proliferation with electrotonic or paracrine effects on neighboring myocytes. The study found that the occurrence of gap junction remodeling and the subsequent conduction slowing in the fibrotic lesions was a necessary but not sufficient condition for AF development, whereas myofibroblast proliferation and the subsequent electrophysiological effect on neighboring myocytes within the fibrotic lesions was the sufficient condition necessary for reentry formation. Collagen did not alter the arrhythmogenic outcome resulting from the other fibrosis components. Reentrant circuits formed throughout the noncontiguous fibrotic lesions, without anchoring to a specific fibrotic lesion.

Modeling 4D changes in pathological anatomy using domain adaptation: analysis of TBI imaging using a tumor database
Bo Wang, M. Prastawa, A. Saha, S.P. Awate, A. Irimia, M.C. Chambers, P.M. Vespa, J.D. Van Horn, V. Pascucci, G. Gerig. In Proceedings of the 2013 MICCAI-MBIA Workshop, Lecture Notes in Computer Science (LNCS), Vol. 8159, Note: Awarded Best Paper!, pp. 31--39. 2013.
DOI: 10.1007/978-3-319-02126-3_4

Analysis of 4D medical images presenting pathology (i.e., lesions) is signi cantly challenging due to the presence of complex changes over time. Image analysis methods for 4D images with lesions need to account for changes in brain structures due to deformation, as well as the formation and deletion of new structures (e.g., edema, bleeding) due to the physiological processes associated with damage, intervention, and recovery. We propose a novel framework that models 4D changes in pathological anatomy across time, and provides explicit mapping from a healthy template to subjects with pathology. Moreover, our framework uses transfer learning to leverage rich information from a known source domain, where we have a collection of completely segmented images, to yield effective appearance models for the input target domain. The automatic 4D segmentation method uses a novel domain adaptation technique for generative kernel density models to transfer information between different domains, resulting in a fully automatic method that requires no user interaction. We demonstrate the effectiveness of our novel approach with the analysis of 4D images of traumatic brain injury (TBI), using a synthetic tumor database as the source domain.

Atrial Fibrosis Quantified Using Late Gadolinium Enhancement MRI is AssociatedWith Sinus Node Dysfunction Requiring Pacemaker Implant
N.W. Akoum, C.J. McGann, G. Vergara, T. Badger, R. Ranjan, C. Mahnkopf, E.G. Kholmovski, R.S. Macleod, N.F. Marrouche. In Journal of Cardiovascular Electrophysiology, Vol. 23, No. 1, pp. 44--50. 2012.
DOI: 10.1111/j.1540-8167.2011.02140.x

Atrial Fibrosis and Sinus Node Dysfunction. Introduction: Sinus node dysfunction (SND) commonly manifests with atrial arrhythmias alternating with sinus pauses and sinus bradycardia. The underlying process is thought to be because of atrial fibrosis. We assessed the value of atrial fibrosis, quantified using Late Gadolinium Enhanced-MRI (LGE-MRI), in predicting significant SND requiring pacemaker implant.

Methods: Three hundred forty-four patients with atrial fibrillation (AF) presenting for catheter ablation underwent LGE-MRI. Left atrial (LA) fibrosis was quantified in all patients and right atrial (RA) fibrosis in 134 patients. All patients underwent catheter ablation with pulmonary vein isolation with posterior wall and septal debulking. Patients were followed prospectively for 329 ± 245 days. Ambulatory monitoring was instituted every 3 months. Symptomatic pauses and bradycardia were treated with pacemaker implantation per published guidelines.

Results: The average patient age was 65 ± 12 years. The average wall fibrosis was 16.7 ± 11.1% in the LA, and 5.3 ± 6.4% in the RA. RA fibrosis was correlated with LA fibrosis (R2= 0.26; P < 0.01). Patients were divided into 4 stages of LA fibrosis (Utah I: 35%). Twenty-two patients (mean atrial fibrosis, 23.9%) required pacemaker implantation during follow-up. Univariate and multivariate analysis identified LA fibrosis stage (OR, 2.2) as a significant predictor for pacemaker implantation with an area under the curve of 0.704.

Conclusions: In patients with AF presenting for catheter ablation, LGE-MRI quantification of atrial fibrosis demonstrates preferential LA involvement. Significant atrial fibrosis is associated with clinically significant SND requiring pacemaker implantation. (J Cardiovasc Electrophysiol, Vol. 23, pp. 44-50, January 2012)

30 Generation of Cloned Transgenic Goats with Cardiac Specific Overexpression of Transforming Growth Factor β1
Q. Meng, J. Hall, H. Rutigliano, X. Zhou, B.R. Sessions, R. Stott, K. Panter, C.J. Davies, R. Ranjan, D. Dosdall, R.S. MacLeod, N. Marrouche, K.L. White, Z. Wang, I.A. Polejaeva. In Reproduction, Fertility and Development, Vol. 25, No. 1, pp. 162--163. 2012.
DOI: 10.1071/RDv25n1Ab30

Transforming growth factor β1 (TGF-β1) has a potent profibrotic function and is central to signaling cascades involved in interstitial fibrosis, which plays a critical role in the pathobiology of cardiomyopathy and contributes to diastolic and systolic dysfunction. In addition, fibrotic remodeling is responsible for generation of re-entry circuits that promote arrhythmias (Bujak and Frangogiannis 2007 Cardiovasc. Res. 74, 184–195). Due to the small size of the heart, functional electrophysiology of transgenic mice is problematic. Large transgenic animal models have the potential to offer insights into conduction heterogeneity associated with fibrosis and the role of fibrosis in cardiovascular diseases. The goal of this study was to generate transgenic goats overexpressing an active form of TGFβ-1 under control of the cardiac-specific α-myosin heavy chain promoter (α-MHC). A pcDNA3.1DV5-MHC-TGF-β1cys33ser vector was constructed by subcloning the MHC-TGF-β1 fragment from the plasmid pUC-BM20-MHC-TGF-β1 (Nakajima et al. 2000 Circ. Res. 86, 571–579) into the pcDNA3.1D V5 vector. The Neon transfection system was used to electroporate primary goat fetal fibroblasts. After G418 selection and PCR screening, transgenic cells were used for SCNT. Oocytes were collected by slicing ovaries from an abattoir and matured in vitro in an incubator with 5% CO2 in air. Cumulus cells were removed at 21 to 23 h post-maturation. Oocytes were enucleated by aspirating the first polar body and nearby cytoplasm by micromanipulation in Hepes-buffered SOF medium with 10 µg of cytochalasin B mL–1. Transgenic somatic cells were individually inserted into the perivitelline space and fused with enucleated oocytes using double electrical pulses of 1.8 kV cm–1 (40 µs each). Reconstructed embryos were activated by ionomycin (5 min) and DMAP and cycloheximide (CHX) treatments. Cloned embryos were cultured in G1 medium for 12 to 60 h in vitro and then transferred into synchronized recipient females. Pregnancy was examined by ultrasonography on day 30 post-transfer. A total of 246 cloned embryos were transferred into 14 recipients that resulted in production of 7 kids. The pregnancy rate was higher in the group cultured for 12 h compared with those cultured 36 to 60 h [44.4% (n = 9) v. 20% (n = 5)]. The kidding rates per embryo transferred of these 2 groups were 3.8% (n = 156) and 1.1% (n = 90), respectively. The PCR results confirmed that all the clones were transgenic. Phenotype characterization [e.g. gene expression, electrocardiogram (ECG), and magnetic resonance imaging (MRI)] is underway. We demonstrated successful production of transgenic goat via SCNT. To our knowledge, this is the first transgenic goat model produced for cardiovascular research.

GSVD Comparison of Patient-Matched Normal and Tumor aCGH Profiles Reveals Global Copy-Number Alterations Predicting Glioblastoma Multiforme Survival
C.H. Lee, B.O. Alpert, P. Sankaranarayanan, O. Alter. In PLoS ONE, Vol. 7, No. 1, Public Library of Science, pp. e30098. 2012.
DOI: 10.1371/journal.pone.0030098

Despite recent large-scale profiling efforts, the best prognostic predictor of glioblastoma multiforme (GBM) remains the patient's age at diagnosis. We describe a global pattern of tumor-exclusive co-occurring copy-number alterations (CNAs) that is correlated, possibly coordinated with GBM patients' survival and response to chemotherapy. The pattern is revealed by GSVD comparison of patient-matched but probe-independent GBM and normal aCGH datasets from The Cancer Genome Atlas (TCGA). We find that, first, the GSVD, formulated as a framework for comparatively modeling two composite datasets, removes from the pattern copy-number variations (CNVs) that occur in the normal human genome (e.g., female-specific X chromosome amplification) and experimental variations (e.g., in tissue batch, genomic center, hybridization date and scanner), without a-priori knowledge of these variations. Second, the pattern includes most known GBM-associated changes in chromosome numbers and focal CNAs, as well as several previously unreported CNAs in greater than 3% of the patients. These include the biochemically putative drug target, cell cycle-regulated serine/threonine kinase-encoding TLK2, the cyclin E1-encoding CCNE1, and the Rb-binding histone demethylase-encoding KDM5A. Third, the pattern provides a better prognostic predictor than the chromosome numbers or any one focal CNA that it identifies, suggesting that the GBM survival phenotype is an outcome of its global genotype. The pattern is independent of age, and combined with age, makes a better predictor than age alone. GSVD comparison of matched profiles of a larger set of TCGA patients, inclusive of the initial set, confirms the global pattern. GSVD classification of the GBM profiles of an independent set of patients validates the prognostic contribution of the pattern.

Analysis of the Criteria of Activation-Based Inverse Electrocardiography using Convex Optimization
B. Erem, P.M. van Dam, D.H. Brooks. In Conf Proc IEEE Eng Med Biol Soc, pp. 3913–3916. 2011.
DOI: 10.1109/IEMBS.2011.6090972
PubMed ID: 22255195

In inverse electrocardiography (ECG), the problem of finding activation times on the heart noninvasively from body surface potentials is typically formulated as a nonlinear least squares optimization problem. Current solutions rely on iterative algorithms which are sensitive to the presence of local minima. As a result, improved initialization approaches for this problem have been of considerable interest. However, in experiments conducted on a subject with Wolff-Parkinson-White syndrome, we have observed that there may be a mismatch between favorable solutions of the optimization problem and solutions with the desired physiological characteristics. In this work, we use a method based on a convex optimization framework to explore the solution space and analyze whether the optimization criteria target their intended objective.

A Conservered Developmental Patterning Network Produces Quantitatively Different Output in Multiple Species of Drosophila
C. Fowlkes, K. Eckenrode, M. Bragdon, M.D. Meyer, Z. Wunderlich, L. Simirenko, C. Luengo, S. Keranen, C. Henriquez, D. Knowles, M. Biggin, M. Eisen, A. DePace. In PLoS Genetics, Vol. 7, No. 10:e1002346, pp. 17 pages. October, 2011.

Differences in the level, timing, or location of gene expression can contribute to alternative phenotypes at the molecular and organismal level. Understanding the origins of expression differences is complicated by the fact that organismal morphology and gene regulatory networks could potentially vary even between closely related species. To assess the scope of such changes, we used high-resolution imaging methods to measure mRNA expression in blastoderm embryos of Drosophila yakuba and Drosophila pseudoobscura and assembled these data into cellular resolution atlases, where expression levels for 13 genes in the segmentation network are averaged into species-specific, cellular resolution morphological frameworks. We demonstrate that the blastoderm embryos of these species differ in their morphology in terms of size, shape, and number of nuclei. We present an approach to compare cellular gene expression patterns between species, while accounting for varying embryo morphology, and apply it to our data and an equivalent dataset for Drosophila melanogaster. Our analysis reveals that all individual genes differ quantitatively in their spatio-temporal expression patterns between these species, primarily in terms of their relative position and dynamics. Despite many small quantitative differences, cellular gene expression profiles for the whole set of genes examined are largely similar. This suggests that cell types at this stage of development are conserved, though they can differ in their relative position by up to 3-4 cell widths and in their relative proportion between species by as much as 5-fold. Quantitative differences in the dynamics and relative level of a subset of genes between corresponding cell types may reflect altered regulatory functions between species. Our results emphasize that transcriptional networks can diverge over short evolutionary timescales and that even small changes can lead to distinct output in terms of the placement and number of equivalent cells.

Tensor Decomposition Reveals Concurrent Evolutionary Convergences and Divergences and Correlations with Structural Motifs in Ribosomal RNA
C. Muralidhara, A.M. Gross, R.R. Gutell, O. Alter. In PLoS ONE, Vol. 6, No. 4, Public Library of Science, pp. e18768. April, 2011.
DOI: 10.1371/journal.pone.0018768

Evolutionary relationships among organisms are commonly described by using a hierarchy derived from comparisons of ribosomal RNA (rRNA) sequences. We propose that even on the level of a single rRNA molecule, an organism's evolution is composed of multiple pathways due to concurrent forces that act independently upon different rRNA degrees of freedom. Relationships among organisms are then compositions of coexisting pathway-dependent similarities and dissimilarities, which cannot be described by a single hierarchy. We computationally test this hypothesis in comparative analyses of 16S and 23S rRNA sequence alignments by using a tensor decomposition, i.e., a framework for modeling composite data. Each alignment is encoded in a cuboid, i.e., a third-order tensor, where nucleotides, positions and organisms, each represent a degree of freedom. A tensor mode-1 higher-order singular value decomposition (HOSVD) is formulated such that it separates each cuboid into combinations of patterns of nucleotide frequency variation across organisms and positions, i.e., "eigenpositions" and corresponding nucleotide-specific segments of "eigenorganisms," respectively, independent of a-priori knowledge of the taxonomic groups or rRNA structures. We find, in support of our hypothesis that, first, the significant eigenpositions reveal multiple similarities and dissimilarities among the taxonomic groups. Second, the corresponding eigenorganisms identify insertions or deletions of nucleotides exclusively conserved within the corresponding groups, that map out entire substructures and are enriched in adenosines, unpaired in the rRNA secondary structure, that participate in tertiary structure interactions. This demonstrates that structural motifs involved in rRNA folding and function are evolutionary degrees of freedom. Third, two previously unknown coexisting subgenic relationships between Microsporidia and Archaea are revealed in both the 16S and 23S rRNA alignments, a convergence and a divergence, conferred by insertions and deletions of these motifs, which cannot be described by a single hierarchy. This shows that mode-1 HOSVD modeling of rRNA alignments might be used to computationally predict evolutionary mechanisms.

Echocardiographic left atrial reverse remodeling after catheter ablation of atrial fibrillation is predicted by preablation delayed enhancement of left atrium by magnetic resonance imaging
S.S. Kuppahally, N. Akoum, T.J. Badger, N.S. Burgon, T. Haslam, E. Kholmovski, R.S. Macleod, C. McGann, N.F. Marrouche. In American Heart Journal, Vol. 160, No. 5, pp. 877--884. 2010.
DOI: 10.1016/j.ahj.2010.07.003
PubMed ID: 21095275

Atrial fibrosis is a hallmark of atrial structural remodeling (SRM) and leads to structural and functional impairment of left atrial (LA) and persistence of atrial fibrillation (AF). This study was conducted to assess LA reverse remodeling after catheter ablation of AF in mild and moderate-severe LA SRM.

Catheter ablation was performed in 68 patients (age 62 ± 14 years, 68% males) with paroxysmal (n = 26) and persistent (n = 42) AF. The patients were divided into group 1 with mild LA SRM (10%, n = 37) by delayed enhancement magnetic resonance imaging (DEMRI). Two-dimensional echocardiography, LA strain, and strain rate during left ventricular systole by velocity vector imaging were performed pre and at 6 ± 3 months postablation. The long-term outcome was monitored for 12 months.

Patients in group 1 were younger (57 ± 15 vs 66 ± 13 years, P = .009) with a male predominance (80% vs 57%, P < .05) as compared to group 2. Postablation, group 1 had significant increase in average LA strain (??: 14% vs 4%, P < .05) and strain rate (??: 0.5 vs 0.1 cm/s, P < .05) as compared to group 2. There was a trend toward more patients with persistent AF in group 2 (68% vs 55%, P = .2), but it was not statistically significant. Group 2 had more AF recurrences (41% vs 16%, P = .02) at 12 months after ablation.

Mild preablation LA SRM by DEMRI predicts favorable LA structural and functional reverse remodeling and long-term success after catheter ablation of AF, irrespective of the paroxysmal or persistent nature of AF.

Resolution Strategies for the Finite-Element-Based Solution of the ECG Inverse Problem
D.F. Wang, R.M. Kirby, C.R. Johnson. In IEEE Transactions on Biomedical Engineering, Vol. 57, No. 2, pp. 220--237. February, 2010.

Global Effects of DNA Replication and DNA Replication Origin Activity on Eukaryotic Gene Expression
L. Omberg, J.R. Meyerson, K. Kobayashi, L.S. Drury, J.F.X. Diffley, O. Alter. In Nature Molecular Systems Biology, Vol. 5, No. 312, pp. (published online). October, 2009.
DOI: 10.1038/msb.2009.70

A Tensor Higher-Order Singular Value Decomposition for Integrative Analysis of DNA Microarray Data From Different Studies
L. Omberg, G.H. Golub, O. Alter. In Proceedings of the National Academy of Sciences, Vol. 104, No. 47, pp. 18371–-18376. November, 2007.
DOI: 10.1073/pnas.0709146104