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Gene Expression Profiling of B Cell Chronic Lymphocytic Leukemia Reveals a Homogeneous Phenotype Related to Memory B Cells 〉
B cell–derived chronic lymphocytic leukemia (B-CLL) represents a common malignancy whose cell derivation and pathogenesis are unknown. Recent studies have shown that >50% of CLLs display hypermutatedExpand
Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference
We propose a new conceptualization of the continual learning problem in terms of a temporally symmetric trade-off between transfer and interference that can be optimized by enforcing gradient alignment across examples. Expand
A modular gradient-sensing network for chemotaxis in Escherichia coli revealed by responses to time-varying stimuli
The Escherichia coli chemotaxis‐signaling pathway computes time derivatives of chemoeffector concentrations. This network features modules for signal reception/amplification and robust adaptation,Expand
Transcriptional analysis of the B cell germinal center reaction
The germinal center (GC) reaction is crucial for T cell-dependent immune responses and is targeted by B cell lymphomagenesis. Here we analyzed the transcriptional changes that occur in B cells duringExpand
Modeling the chemotactic response of Escherichia coli to time-varying stimuli
In their natural environment, cells need to extract useful information from complex temporal signals that vary over a wide range of intensities and time scales. Here, we study how such signals areExpand
Hydrodynamics and phases of flocks
Abstract We review the past decade’s theoretical and experimental studies of flocking: the collective, coherent motion of large numbers of self-propelled “particles” (usually, but not always, livingExpand
Flocks, herds, and schools: A quantitative theory of flocking
We present a quantitative continuum theory of ``flocking'': the collective coherent motion of large numbers of self-propelled organisms. In agreement with everyday experience, our model predicts theExpand
Analysis of Gene Expression Microarrays for Phenotype Classification
We propose a supervised learning algorithm based on a non-linear similarity metric, which maximizes the probability of discovering discriminative gene expression patterns in the phenotype set. Expand
Quantitative Modeling of Escherichia coli Chemotactic Motion in Environments Varying in Space and Time
We find that the cell's chemotaxis drift velocity vd is a constant in an exponential attractant concentration gradient [L]∝exp(Gx). Expand
Quantitative noise analysis for gene expression microarray experiments
A major challenge in DNA microarray analysis is to effectively dissociate actual gene expression values from experimental noise. We report here a detailed noise analysis for oligonuleotide-basedExpand