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Search Results: 1 - 10 of 193449 matches for " Clark D Jeffries "
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Gene processing control loops suggested by sequencing, splicing, and RNA folding
Clark D Jeffries, Diana O Perkins, Xiaojun Guan
BMC Bioinformatics , 2010, DOI: 10.1186/1471-2105-11-602
Abstract: Deep sequencing technology has enabled discovery of a novel 16-nt RNA sequence in total RNA from human brain that we propose is derived from RNU1, an RNA component of spliceosome assembly. Bioinformatic alignments compel inquiring whether the novel 16-nt sequence or its precursor have a regulatory function as well as determining aspects of how processing intersects with the miRNA biogenesis pathway. Specifically, our preliminary in silico investigations reveal the sequence could regulate splicing factor Arg/Ser rich 1 (SFRS1), a gene coding an essential protein component of the spliceosome. All 16-base source sequences in the UCSC Human Genome Browser are within the 14 instances of RNU1 genes listed in wgEncodeGencodeAutoV3. Furthermore, 10 of the 14 instances of the sequence are also within a common 28-nt hairpin-forming subsequence of RNU1.An abundant 16-nt RNA sequence is sourced from a spliceosomal RNA, lies in a stem of a predicted RNA hairpin, and includes reverse complements of subsequences of the 3'UTR of a gene coding for a spliceosome protein. Thus RNU1 could function both as a component of spliceosome assembly and as inhibitor of production of the essential, spliceosome protein coded by SFRS1. Beyond this example, a general procedure is needed for systematic discovery of multiple alignments of sequencing, splicing, and RNA folding data.The numerous, very dissimilar types of bioinformatic data conspire to make integration a central problem for efficient and effective application of biological findings. Integration of data of three particular types is the goal of this paper. Gene splicing is the focus, held up as an example of how sequencing, splicing, and RNA folding data types might be used to guide research that could illuminate major mechanisms of cell biology such control of levels of ribonucleoprotein species.Function and dysfunction of gene splicing impact embryogenesis, cell motility and viability, cell cycle arrest, and many other mechanisms of met
Discovering collectively informative descriptors from high-throughput experiments
Clark D Jeffries, William O Ward, Diana O Perkins, Fred A Wright
BMC Bioinformatics , 2009, DOI: 10.1186/1471-2105-10-431
Abstract: This paper describes a novel algorithm called BLANKET for symmetric analysis of two experiments that assess informativeness of descriptors. The experiments are required to be related only in that their descriptor sets intersect substantially and their definitions of case and control are consistent. From resulting lists of n descriptors ranked by informativeness, BLANKET determines shortlists of descriptors from each experiment, generally of different lengths p and q. For any pair of shortlists, four numbers are evident: the number of descriptors appearing in both shortlists, in exactly one shortlist, or in neither shortlist. From the associated contingency table, BLANKET computes Right Fisher Exact Test (RFET) values used as scores over a plane of possible pairs of shortlist lengths [1,2]. BLANKET then chooses a pair or pairs with RFET score less than a threshold; the threshold depends upon n and shortlist length limits and represents a quality of intersection achieved by less than 5% of random lists.Researchers seek within a universe of descriptors some minimal subset that collectively and efficiently predicts experimental outcomes. Ideally, any smaller subset should be insufficient for reliable prediction and any larger subset should have little additional accuracy. As a method, BLANKET is easy to conceptualize and presents only moderate computational complexity. Many existing databases could be mined using BLANKET to suggest optimal sets of predictive descriptors.In contemporary high-throughput experiments, very many descriptor values can be measured, leading to the issue of correction for multiple testing to minimize false positives at the cost of a high number of false negatives. Reconciliation entails compromises that are to some extent arbitrary. A deterministic method is needed for selecting a minimal, distinguished set of descriptors that collectively provide effective, efficient prediction. Researchers can subsequently investigate members of such a subset
A Flexible and Qualitatively Stable Model for Cell Cycle Dynamics Including DNA Damage Effects
Clark D. Jeffries, Charles R. Johnson, Tong Zhou, Dennis A. Simpson and William K. Kaufmann
Gene Regulation and Systems Biology , 2012, DOI: 10.4137/GRSB.S8476
Abstract: This paper includes a conceptual framework for cell cycle modeling into which the experimenter can map observed data and evaluate mechanisms of cell cycle control. The basic model exhibits qualitative stability, meaning that regardless of magnitudes of system parameters its instances are guaranteed to be stable in the sense that all feasible trajectories converge to a certain trajectory. Qualitative stability can also be described by the signs of real parts of eigenvalues of the system matrix. On the biological side, the resulting model can be tuned to approximate experimental data pertaining to human fibroblast cell lines treated with ionizing radiation, with or without disabled DNA damage checkpoints. Together these properties validate a fundamental, first order systems view of cell dynamics. Classification Codes: 15A68
A Flexible and Qualitatively Stable Model for Cell Cycle Dynamics Including DNA Damage Effects
Clark D. Jeffries,Charles R. Johnson,Tong Zhou,Dennis A. Simpson
Gene Regulation and Systems Biology , 2012,
microRNA expression in the prefrontal cortex of individuals with schizophrenia and schizoaffective disorder
Diana O Perkins, Clark D Jeffries, L Fredrik Jarskog, J Michael Thomson, Keith Woods, Martin A Newman, Joel S Parker, Jianping Jin, Scott M Hammond
Genome Biology , 2007, DOI: 10.1186/gb-2007-8-2-r27
Abstract: We hypothesized that schizophrenia might be associated with altered miRNA profiles. To investigate this possibility we compared the expression of 264 human miRNAs from postmortem prefrontal cortex tissue of individuals with schizophrenia (n = 13) or schizoaffective disorder (n = 2) to tissue of 21 psychiatrically unaffected individuals using a custom miRNA microarray. Allowing a 5% false discovery rate, we found that 16 miRNAs were differentially expressed in prefrontal cortex of patient subjects, with 15 expressed at lower levels (fold change 0.63 to 0.89) and 1 at a higher level (fold change 1.77) than in the psychiatrically unaffected comparison subjects. The expression levels of 12 selected miRNAs were also determined by quantitative RT-PCR in our lab. For the eight miRNAs distinguished by being expressed at lower microarray levels in schizophrenia samples versus comparison samples, seven were also expressed at lower levels with quantitative RT-PCR.This study is the first to find altered miRNA profiles in postmortem prefrontal cortex from schizophrenia patients.Schizophrenia is a common neuropsychiatric disorder affecting one percent of the general population. The personal, familial, and societal costs of the disease are enormous, with chronic symptoms that result in marked functional disability. In fact, approximately three percent of all person-years lived with disability are due to schizophrenia [1].It is clear that schizophrenia has a strong genetic component, although its genetic basis remains unknown [2]. Consistent with a disease mechanism that involves post-transcriptional dysregulation of gene expression, postmortem studies find altered levels of mRNA and proteins rather than a specific abnormal protein [3]. Postmortem studies also find differences between schizophrenia and unaffected comparison subjects in the relationship of such mRNAs and cognate proteins [4,5].microRNAs (miRNAs) are a class of noncoding RNAs (ncRNAs) that in animals regulate gene ex
X-rays from Open Clusters
R. D. Jeffries
Physics , 1998,
Abstract: The present state of X-ray observations of cool stars in coeval open clusters is reviewed. Concentrating on ROSAT results for solar-type stars, the available observational dataset is summarized along with those details of the evolution of X-ray activity of low mass stars which have been firmly established as a result. Observational questions which are as yet unresolved are then addressed, including the origin of ``supersaturation'' and whether observations of one cluster can represent the X-ray properties of all clusters at the same age. The role of high spatial resolution X-ray imaging as a tool for identifying cluster members is highlighted and the prospects for future developments with AXAF and XMM are discussed.
Measuring the Initial Mass Function of Low Mass Stars and Brown Dwarfs
R. D. Jeffries
Physics , 2012, DOI: 10.1051/eas/1257002
Abstract: I review efforts to determine the form and any lower limit to the initial mass function in the Galactic disk, using observations of low-mass stars and brown dwarfs in the field, young clusters and star forming regions. I focus on the methodologies that have been used and the uncertainties that exist due to observational limitations and to systematic uncertainties in calibrations and theoretical models. I conclude that whilst it is possible that the low-mass IMFs deduced from the field and most young clusters are similar, there are too many problems to be sure; there are examples of low-mass cluster IMFs that appear to be very discrepant and the IMFs for brown dwarfs in the field and young clusters have yet to be reconciled convincingly.
Are There Age Spreads in Star Forming Regions?
R. D. Jeffries
Physics , 2011, DOI: 10.1007/978-3-642-22113-2_23
Abstract: A luminosity spread at a given effective temperature is ubiquitously seen in the Hertzsprung-Russell (HR) diagrams of young star forming regions and often interpreted in terms of a prolonged period (>=10 Myr) of star formation. I review the evidence that the observed luminosity spreads are genuine and not caused by astrophysical sources of scatter. I then address whether the luminosity spreads necessarily imply large age spreads, by comparing HR diagram ages with ages from independent clocks such as stellar rotation rate, the presence of circumstellar material and lithium depletion. I argue that whilst there probably is a true luminosity dispersion, there is little evidence to support age spreads larger than a few Myr. This paradox could be resolved by brief periods of rapid accretion during the class I pre main-sequence phase.
Lithium depletion in open clusters
R. D. Jeffries
Physics , 1999,
Abstract: The current status of observational studies of lithium depletion in open clusters is reviewed, concentrating mainly on G and K type stars. I attempt to answer the following questions: Can the lithium depletion patterns seen in open clusters be explained in terms of standard stellar evolution models? What is the observational evidence for non-standard mixing processes and on what timescales do they operate? Does metallicity play a significant role in lithium depletion? Can lithium still be used as a means of dating young stars? What future observations might yield better answers to these questions?
On the lithium abundance dispersion in late-type Pleiades stars
R. D. Jeffries
Physics , 1999, DOI: 10.1046/j.1365-8711.1999.02822.x
Abstract: I present the results of a programme to monitor the strengths of the Li I 6708A, K I 7699A and chromospheric Halpha lines in a group of cool Pleiades stars. Consistent instrumentation and analysis techniques are used to show that there is no Li I variability on timescales of 1 year that could possibly account for the apparent spread in Li abundances seen in Pleiades stars between effective temperatures of 4800-5200K. Comparison with published data reveals tentative evidence for variability on 10 year timescales, but at a very low level. The lack of chromospheric activity variability above levels of 20 to 30 percent makes it difficult however, to rule out evenly distributed magnetic activity regions causing a scatter in the Li I line strengths at a given abundance. The similar star to star scatter of K I line strengths in these and published data reinforces the conclusion that it is still unsafe to attribute the Li I line strength dispersion to a large variation in Li depletion at a given mass.
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