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Eytan Domany

Publications and source records attributed to Eytan Domany.

At least 37 records · Page 2Linked to original sources
arXiv2004

Functional immunomics: Microarray analysis of IgG autoantibody repertoires predicts the future response of NOD mice to an inducer of accelerated diabetes

One's present repertoire of antibodies encodes the history of one's past immunological experience. Can the present autoantibody repertoire be consulted to predict resistance or susceptibility to the future development of an autoimmune disease? Here we developed an antigen microarray chip and used bioinformatic analysis to study a model of type 1 diabetes developing in non-obese diabetic (NOD) male mice in which the disease was accelerated and synchronized by exposing the mice to cyclophosphamide at 4 weeks of age. We obtained sera from 19 individual mice, treated the mice to induce cyclophosphamide-accelerated diabetes (CAD), and found, as expected, that 9 mice became severely diabetic while 10 mice permanently resisted diabetes. We again obtained serum from each mouse afterCAD induction. We then analyzed the patterns of antibodies in the individualmice to 266 different antigens spotted on the antigen chip. We identified a select panel of 27 different antigens (10% of the array) that revealed a pattern of IgG antibody reactivity in the pre-CAD serathat discriminated between the mice resistant or susceptible to CAD with 100% sensitivity and 82% specificity (p=0.017). Surprisingly, the set of IgG antibodies that was informative before CAD induction did not separate the resistant and susceptible groups after the onset of CAD; new antigens became criticalfor post-CAD repertoire discrimination. Thus, at least for a model disease, present antibody repertoires can predict future disease; predictive and diagnostic repertoires can differ; and decisive information about immune system behavior can be mined by bioinformatic technology. Repertoires matter.

q-bio.TO↗
arXiv2004

Design Principle of Gene Expression Used by Human Stem Cells; Implication for Pluripotency

Human embryonic stem cells (ESC) are undifferentiated and are endowed with the capacities of self renewal and pluripotential differentiation. Adult stem cells renew their own tissue, but whether they can trans-differentiate to other tissues is still controversial. To understand the genetic program that underlies the pluripotency of stem cells, we compared the transcription profile of ESC with that of progenitor/stem cells of human hematopoietic and keratinocytic origins, along with their mature cells to be viewed as snapshots along tissue differentiation. ESC gene profile show higher complexity with significantly more highly expressed genes than adult cells. We hypothesize that ESC use a strategy of expressing genes that represent various differentiation pathways and selection of only a few for continuous expression upon differentiation to a particular target. Such a strategy may be necessary for the pluripotency of ESC. The progenitors of either hematopoietic or keratinocytic cells also follow the same design principle. Using advanced clustering, we show that many of the ESC expressed genes are turned off in the progenitors/stem cells followed by a further downregulation in adult tissues. Concomitantly, genes specific to the target tissue are upregulated towards matured cells of skin or blood.

q-bio.QM↗
arXiv2004

FSSP to SCOP and CATH (F2CS) Prediction Server

Summary: The F2CS server provides access to the software, F2CS2.00, that implements an automated prediction method of SCOP and CATH classifications of proteins, based on their FSSP Z-scores (Getz et al., 2002), Availability: Free, at http://www.weizmann.ac.il/physics/complex/compphys/f2cs/. Contact: eytan.domany@weizmann.ac.il Supplementary information: The site contains links to additional figures and tables.

q-bio.BM↗
arXiv2004

Outcome signature genes in breast cancer: is there a unique set?

Motivation: Predicting the metastatic potential of primary malignant tissues has direct bearing on choice of therapy. Several microarray studies yielded gene sets whose expression profiles successfully predicted survival (Ramaswamy et al 2003; Sorlie et al 2001; van't Veer et al 2003). Nevertheless, the overlap between these gene sets is almost zero. Such small overlaps were observed also in other complex diseases (Lossos et al 2003; Miklos and Maleszka 2004), and the variables that could account for the differences had evoked a wide interest. One of the main open questions in this context is whether the disparity can be attributed only to trivial reasons such as different technologies, different patients and different types of analysis. Results: To answer this question we concentrated on one single breast cancer dataset, and analyzed it by one single method, the one which was used by van't Veer et al to produce a set of outcome predictive genes. We showed that in fact the resulting set of genes is not unique; it is strongly influenced by the subset of patients used for gene selection. Many equally predictive lists could have been produced from the same analysis. Three main properties of the data explain this sensitivity: (a) many genes are correlated with survival; (b) the differences between these correlations are small; (c) the correlations fluctuate strongly when measured over different subsets of patients. A possible biological explanation for these properties is discussed.

q-bio.QM↗
arXiv2004

Lack of Ultrametricity in the Low-Temperature phase of 3D Ising Spin Glasses

We study the low-temperature spin-glass phases of the Sherrington-Kirkpatrick (SK) model and of the 3-dimensional short range Ising spin glass (3dISG). For the SK model, evidence for ultrametricity becomes clearer as the system size increases, while for the short-range case our results indicate the opposite, i.e. lack of ultrametricity. Our results are obtained by a recently proposed method that uses clustering to focus on the relevant parts of phase space and reduce finite size effects. Evidence that the mean field solution does not apply in detail to the 3dISG is also found by another method which does not rely on clustering.

cond-mat.dis-nn↗
arXiv2002

Cluster Analysis of Gene Expression Data

The expression levels of many thousands of genes can be measured simultaneously by DNA microarrays (chips). This novel experimental tool has revolutionized research in molecular biology and generated considerable excitement. A typical experiment uses a few tens of such chips, each dedicated to a single sample - such as tissue extracted from a particular tumor. The results of such an experiment contain several hundred thousand numbers, that come in the form of a table, of several thousand rows (one for each gene) and 50 - 100 columns (one for each sample). We developed a clustering methodology to mine such data. In this review I provide a very basic introduction to the subject, aimed at a physics audience with no prior knowledge of either gene expression or clustering methods. I explain what genes are, what is gene expression and how it is measured by DNA chips. Next I explain what is meant by "clustering" and how we analyze the massive amounts of data from such experiments, and present results obtained from analysis of data obtained from colon cancer, brain tumors and breast cancer.

physics.bio-ph↗
arXiv2002

Coupled Two-Way Clustering Analysis of Breast Cancer and Colon Cancer Gene Expression Data

We present and review Coupled Two Way Clustering, a method designed to mine gene expression data. The method identifies submatrices of the total expression matrix, whose clustering analysis reveals partitions of samples (and genes) into biologically relevant classes. We demonstrate, on data from colon and breast cancer, that we are able to identify partitions that elude standard clustering analysis.

physics.bio-ph↗
arXiv2001

Automated assignment of SCOP and CATH protein structure classification from FSSP scores

We present an automated procedure to assign CATH and SCOP classifications to proteins whose FSSP score is available. CATH classification is assigned down to the topology level and SCOP classification to the fold level. As the FSSP database is updated weekly, this method makes it possible to update also CATH and SCOP with the same frequency. Our predictions have a nearly perfect success rate when ambiguous cases are discarded. These ambiguous cases are intrinsic in any protein structure classification, which relies on structural information alone. Hence, we introduce the notion of ``twilight zone for structure classification''. We further suggest that in order to resolve these ambiguous cases other criteria of classification, based also on information about sequence and function, must be used.

cond-mat.soft↗
arXiv2001

State Hierarchy Induced by Correlated Spin Domains in short range spin glasses

We generate equilibrium configurations for the three and four dimensional Ising spin glass with Gaussian distributed couplings at temperatures well below the transition temperature T_c. These states are analyzed by a recently proposed method using clustering. The analysis reveals a hierarchical state space structure. At each level of the hierarchy states are labeled by the orientations of a set of correlated macroscopic spin domains. Our picture of the low temperature phase of short range spin glasses is that of a State Hierarchy Induced by Correlated Spin domains (SHICS). The complexity of the low temperature phase is manifest in the fact that the composition of such a spin domain (i.e. its constituent spins), as well as its identifying label, are defined and determined by the ``location'' in the state hierarchy at which it appears. Mapping out the phase space structure by means of the orientations assumed by these domains enhances our ability to investigate the overlap distribution, which we find to be non-trivial. Evidence is also presented that these states may have a non-ultrametric structure.

cond-mat.dis-nn↗
arXiv2000

Resampling Method For Unsupervised Estimation Of Cluster Validity

We introduce a method for validation of results obtained by clustering analysis of data. The method is based on resampling the available data. A figure of merit that measures the stability of clustering solutions against resampling is introduced. Clusters which are stable against resampling give rise to local maxima of this figure of merit. This is presented first for a one-dimensional data set, for which an analytic approximation for the figure of merit is derived and compared with numerical measurements. Next, the applicability of the method is demonstrated for higher dimensional data, including gene microarray expression data.

physics.comp-ph↗
arXiv1999

Flowing sand - a physical realization of Directed Percolation

We introduce and investigate a simple model to describe recent experiments by Douady and Daerr on flowing sand. The model reproduces experimentally observed compact avalanches, whose opening angle decreases linearly as a threshold is approached. On large scales the model exhibits a crossover from compact directed percolation to directed percolation; we predict similar behavior for the experimental system. We estimate the regime where "true" directed percolation morphology and exponents will be observed, providing the first experimental realization for this class of models.

cond-mat.stat-mech↗
arXiv1999

Flowing sand - a possible physical realization of Directed Percolation

A simple model for flowing sand on an inclined plane is introduced. The model is related to recent experiments by Douady and Daerr [Nature 399, 241 (1999)] and reproduces some of the experimentally observed features. Avalanches of intermediate size appear to be compact, placing the critical behavior of the model into the universality class of compact directed percolation. On very large scales, however, the avalanches break up into several branches leading to a crossover from compact to ordinary directed percolation. Thus, systems of flowing granular matter on an inclined plane could serve as a first physical realization of directed percolation.

cond-mat.stat-mech↗
arXiv1999

Folding Lennard-Jones proteins by a contact potential

We studied the possibility to approximate a Lennard Jones interaction by a pairwise contact potential. First we used a Lennard-Jones potential to design off-lattice, protein-like heteropolymer sequences, whose lowest energy (native) conformations were then identified by Molecular Dynamics. Then we turned to investigate whether one can find a pairwise contact potential, whose ground states are the contact maps associated with these native conformations. We show that such a requirement cannot be satisfied exactly - i.e. no such contact parameters exist. Nevertheless, we found that one can find contact energy parameters for which an energy minimization procedure, acting in the space of contact maps, yields maps whose corresponding structures are close to the native ones. Finally we show that when these structures are used as the initial point of a Molecular Dynamics energy minimization process, the correct native folds are recovered with high probability.

cond-mat.stat-mech↗
arXiv1999

Protein folding using contact maps

We present the development of the idea to use dynamics in the space of contact maps as a computational approach to the protein folding problem. We first introduce two important technical ingredients, the reconstruction of a three dimensional conformation from a contact map and the Monte Carlo dynamics in contact map space. We then discuss two approximations to the free energy of the contact maps and a method to derive energy parameters based on perceptron learning. Finally we present results, first for predictions based on threading and then for energy minimization of crambin and of a set of 6 immunoglobulins. The main result is that we proved that the two simple approximations we studied for the free energy are not suitable for protein folding. Perspectives are discussed in the last section.

cond-mat.soft↗
arXiv1998

Damage Spreading in a 2D Ising Model with Swendsen-Wang Dynamics

Damage spreading for 2D Ising cluster dynamics is investigated numerically by using random numbers in a way that conforms with the notion of submitting the two evolving replicas to the same thermal noise. Two damage spreading transitions are found; damage does not spread either at low or high temperatures. We determine the critical exponents at the high-temperature transition point, which seem consistent with directed percolation.

cond-mat.stat-mech↗
arXiv1998

Elusive Unfoldability: Learning a Contact Potential to Fold Crambin

We investigate the extent to which the commonly used standard pairwise contact potential can be used to identify the native fold of a protein. Ideally one would hope that a universal energy function exists, for which the native folds of all proteins are the respective ground states. Here we pose a much more restricted question: is it possible to find a set of contact parameters for which the energy of the native contact map of a single protein (crambin) is lower than that of all possible physically realizable decoy maps. We seek such a set of parameters by perceptron learning, a procedure which is guaranteed to find such a set if it exists. We found that it is extremely hard (and most probably, impossible) to fine tune contact parameters that will assign all alternative conformations higher energy than that of the native map. This finding clearly indicates that it is impossible to derive a general pairwise contact potential that can be used to fold any given protein. Inclusion of additional energy terms, such as hydrophobic (solvation), hydrogen bond or multi-body interactions may help to attain foldability within specific structural families.

cond-mat.soft↗