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Fort Lewis, NJ, United States

Lim S.F.,Princeton University | Ryu W.S.,Lewis Sigler Institute for Integrative Genomics | Austin R.H.,Princeton University
Optics Express | Year: 2010

The effects of the nanocrystal size on the emission spectra and decay rates of upconverting hexagonal NaYF4:Yb,Er nanocrystals are investigated. The influence of nanocrystal size is represented in terms of the surface area/volume ratio (SA/Vol). Our results show that a small nanocrystal size, or large SA/Vol ratio increases the decay rate, in particular, the green luminescence decay rate varies linearly with the SA/Vol ratio. © 2009 Optical Society of America. Source

Chikina M.D.,Mount Sinai School of Medicine | Troyanskaya O.G.,Lewis Sigler Institute for Integrative Genomics
Bioinformatics | Year: 2012

Motivation: ChIPseq is rapidly becoming a common technique for investigating protein-DNA interactions. However, results from individual experiments provide a limited understanding of chromatin structure, as various chromatin factors cooperate in complex ways to orchestrate transcription. In order to quantify chromtain interactions, it is thus necessary to devise a robust similarity metric applicable to ChIPseq data. Unfortunately, moving past simple overlap calculations to give statistically rigorous comparisons of ChIPseq datasets often involves arbitrary choices of distance metrics, with significance being estimated by computationally intensive permutation tests whose statistical power may be sensitive to non-biological experimental and post-processing variation. Results: We show that it is in fact possible to compare ChIPseq datasets through the efficient computation of exact P-values for proximity. Our method is insensitive to non-biological variation in datasets such as peak width, and can rigorously model peak location biases by evaluating similarity conditioned on a restricted set of genomic regions (such as mappable genome or promoter regions). Applying our method to the well-studied dataset of Chen et al. (2008), we elucidate novel interactions which conform well with our biological understanding. By comparing ChIPseq data in an asymmetric way, we are able to observe clear interaction differences between cofactors such as p300 and factors that bind DNA directly. © The Author 2012. Published by Oxford University Press. All rights reserved. Source

Xu X.,Duke University | Kumar N.,University of Massachusetts Boston | Krishnan A.,Lewis Sigler Institute for Integrative Genomics | Kulkarni R.V.,University of Massachusetts Boston
Proceedings of the IEEE Conference on Decision and Control | Year: 2013

The process of transcription has been intensively studied for several decades, however there is still much to learn about the underlying biochemcial processes. Recent advances in single-molecule techniques have provided new experimental data that highlights the role of transcriptional pausing in the regulation of gene expression. In some cases, it has been shown that transcriptional pauses are rate-limiting stochastic processes, thus a quantitative understanding requires stochastic modeling of the underlying processes. We propose a coarsegrained stochastic model to analyze the dwell-time distribution for transcriptional pausing. The proposed kinetic scheme can also be used to model transcriptional initiation and to analyze the corresponding noise in gene expression. We obtain analytical solutions which can provide useful insights into current and future experiments focusing on time-resolved single-molecule studies of transcriptional pausing and noise in gene expression. ©2013 IEEE. Source

Mora T.,Lewis Sigler Institute for Integrative Genomics | Mora T.,CNRS ENS Statistical Physics Laboratory | Bai F.,Osaka University | Che Y.-S.,Osaka University | And 4 more authors.
Physical Biology | Year: 2011

By analyzing 30 min, high-resolution recordings of single Escherichia coli flagellar motors in the physiological regime, we show that two main properties of motor switching - the mean clockwise and mean counter-clockwise interval durations - vary significantly. When we represent these quantities on a two-dimensional plot for several cells, the data do not fall on a one-dimensional curve, as expected with a single control parameter, but instead spread in two dimensions, pointing to motor individuality. The largest variations are in the mean counter-clockwise interval, and are attributable to variations in the concentration of the internal signaling molecule CheY-P. In contrast, variations in the mean clockwise interval are interpreted in terms of motor individuality. We argue that the sensitivity of the mean counter-clockwise interval to fluctuations in CheY-P is consistent with an optimal strategy of run and tumble. The concomittent variability in mean run length may allow populations of cells to better survive in rapidly changing environments by 'hedging their bets'. © 2011 IOP Publishing Ltd. Source

Ghersi D.,Lewis Sigler Institute for Integrative Genomics | Singh M.,Lewis Sigler Institute for Integrative Genomics | Singh M.,Princeton University
Bioinformatics | Year: 2014

The chemical structures of biomolecules, whether naturally occurring or synthetic, are composed of functionally important building blocks. Given a set of small molecules - for example, those known to bind a particular protein - computationally decomposing them into chemically meaningful fragments can help elucidate their functional properties, and may be useful for designing novel compounds with similar properties. Here we introduce molBLOCKS, a suite of programs for breaking down sets of small molecules into fragments according to a predefined set of chemical rules, clustering the resulting fragments, and uncovering statistically enriched fragments. Among other applications, our software should be a great aid in large-scale chemical analysis of ligands binding specific targets of interest. © 2014 The Author 2014. Source

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