User:Ahmad A. Mannan

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IMPERIAL BIOMATHS JOURNAL CLUB

We put together a journal club for sharing and discussing papers and problems (theory) of mathematical modelling of biological systems (both stochastically and deterministically).

NEXT GATHERING

  • Date: THURSDAY 17th NOVEMBER
  • Time: 4PM
  • Venue: Huxley 747

COMPILATION OF PAPERS TO READ

Academic Year 2015-2016

  • [X] - Noise in Gene Expression is Coupled to Growth Rate[1]
  • [X] - Division in Escherichia coli is triggered by a size-sensing rather than a timing mechanism[2]
  • [X] - The quantitative and condition-dependent Escherichia coli proteome[3]
  • [X] - Learning (from) the errors of a systems biology model[4]
  • [X] - Dynamics of Epigenetic Regulation at the Single-Cell Level[5]
  • [X] - Emergent genetic oscillations in a synthetic microbial consortium [6]
  • [X] - Cell-Size Control and Homeostasis in Bacteria [7]
  • [X] - Exploiting Nongenetic Cell-to-Cell Variation for Enhanced Biosynthesis [8] - Paper of the lab of Dr Fuzhong Zhang
  • [X] - Constraints on Fluctuations in Sparsely Characterized Biological Systems [9]
  • [X] - Stochastic Activation of a DNA Damage Response Causes Cell-to-Cell Mutation Rate Variation [10]
  • [X] - Overflow metabolism in Escherichia coli results from efficient proteome allocation [11]
  • [X] - Molecular circuits for dynamic noise filtering [12]
  • [X] - Measurement of gene regulation in individual cells reveals rapid switching between promoter states [13]
  • [X] - Cellular Growth Arrest and Persistence from Enzyme Saturation [14]

Academic Year 2016-2017

  • [X] - Creating Single-Copy Genetic Circuits [15]
  • [X] - The Cost of Protein Production [16]
  • [] - Synchronous long-term oscillations in a synthetic gene circuit [17]
  • [] - Bacterial persistence is an active σS stress response to metabolic flux limitation [18]
  • [] - Sugar Synthesis from CO_2 in Escherichia coli [19]
  • [] - Expression noise facilitates the evolution of gene regulation [20]
  • [] - Complex Interplay of Physiology and Selection in the Emergence of Antibiotic Resistance [21]
  • [] - Thresholds and ultrasensitivity from negative cooperativity [22]
  • [] - Exploiting Natural Fluctuations to Identify Kinetic Mechanisms in Sparsely Characterized Systems [23] - Do on or after 23rd June
  • [] - Synchronized mitochondrial and cytosolic translation programs [24] - Do on or after 23rd June
  • [] - Glucose becomes one of the worst carbon sources for E.coli on poor nitrogen sources due to suboptimal levels of cAMP [25]
  • Slow Protein Fluctuations Explain the Emergence of Growth Phenotypes and Persistence in Clonal Bacterial Populations [26]
  • Stress‐response balance drives the evolution of a network module and its host genome [27]
  • Evolutionary consequences of drug resistance: shared principles across diverse targets and organisms [28]
  • A noisy linear map underlies oscillations in cell size and gene expression in bacteria [29]
  • Replication of DNA in bacteria with heterogeneous generation times [30]
  • Duplication of the bacterial cell and its initiation [31]
  • Dilution of the cell cycle inhibitor Whi5 controls budding-yeast cell size [32]
  • A growth‐rate composition formula for the growth of E. coli on co‐utilized carbon substrates [33]
  • Macromolecular Crowding as a Regulator of Gene Transcription [34]
  • Cell Size and the Initiation of DNA Replication in Bacteria [35]
  • How fast-growing bacteria robustly tune their ribosome concentration to approximate growth-rate maximisation [36]
  • Optimization of lag time underlies antibiotic tolerance in evolved bacterial populations [37]
  • Does evolutionary theory need a rethink? [38]
  • A cross-chiral RNA polymerase ribozyme [39]
  • Cell cycle: It takes three to find the exit [40]
  • Loss of growth homeostasis by genetic decoupling of cell division from biomass growth: implication for size control mechanisms [41]
  • Causal signals between codon bias, mRNA structure, and the efficiency of translation and elongation [42]
  • Cell dynamics and gene expression control in tissue homeostasis and development [43]
  • Quantitative evolutionary dynamics using high-resolution lineage tracking [44], with comment HERE
  • Conditional density-based analysis of T cell signaling in single-cell data [45]
  • Evolution of context dependent regulation by expansion of feast/famine regulatory proteins [46]
  • Carbon source-dependent expansion of the genetic code in bacteria [47]
  • Reducing the genetic code induces massive rearrangement of the proteome [48]
  • Conserved codon composition of ribosomal protein coding genes inEscherichia coli, Mycobacterium tuberculosis and Saccharomyces cerevisiae: lessons from supervised machine learning in functional genomics [49]

CONTACT INFORMATION

Please feel free to e-mail me if you would like to suggest another paper to discuss at the group:



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