Michigan Technological University
Education•Houghton, Michigan, United States•
About: Michigan Technological University is a(n) education organization based out in Houghton, Michigan, United States. It is known for research contribution in the topic(s): Population & Volcano. The organization has 8023 authors who have published 17422 publication(s) receiving 481780 citation(s). The organization is also known as: MTU & Michigan Tech.
Papers published on a yearly basis
01 Sep 1999-Genome Research
TL;DR: The third generation of the CAP sequence assembly program is described, which has a capability to clip 5' and 3' low-quality regions of reads and uses forward-reverse constraints to correct assembly errors and link contigs.
Abstract: The shotgun sequencing strategy has been used widely in genome sequencing projects. A major phase in this strategy is to assemble short reads into long sequences. A number of DNA sequence assembly programs have been developed (Staden 1980; Peltola et al. 1984; Huang 1992; Smith et al. 1993; Gleizes and Henaut 1994; Lawrence et al. 1994; Kececioglu and Myers 1995; Sutton et al. 1995; Green 1996). The FAKII program provides a library of routines for each phase of the assembly process (Larson et al. 1996). The GAP4 program has a number of useful interactive features (Bonfield et al. 1995). The PHRAP program clips 5′ and 3′ low-quality regions of reads and uses base quality values in evaluation of overlaps and generation of contig sequences (Green 1996). TIGR Assembler has been used in a number of megabase microbial genome projects (Sutton et al. 1995). Continued development and improvement of sequence assembly programs are required to meet the challenges of the human, mouse, and maize genome projects. We have developed the third generation of the CAP sequence assembly program (Huang 1992). The CAP3 program includes a number of improvements and new features. A capability to clip 5′ and 3′ low-quality regions of reads is included in the CAP3 program. Base quality values produced by PHRED (Ewing et al. 1998) are used in computation of overlaps between reads, construction of multiple sequence alignments of reads, and generation of consensus sequences. Efficient algorithms are employed to identify and compute overlaps between reads. Forward–reverse constraints are used to correct assembly errors and link contigs. Results of CAP3 on four BAC data sets are presented. The performance of CAP3 was compared with that of PHRAP on a number of BAC data sets. PHRAP often produces longer contigs than CAP3 whereas CAP3 often produces fewer errors in consensus sequences than PHRAP. It is easier to construct scaffolds with CAP3 than with PHRAP on low-pass data with forward–reverse constraints. An unusual feature of CAP3 is the use of forward–reverse constraints in the construction of contigs. A forward–reverse constraint is often produced by sequencing of both ends of a subclone. A forward–reverse constraint specifies that the two reads should be on the opposite strands of the DNA molecule within a specified range of distance. By sequencing both ends of each subclone, a large number of forward–reverse constraints are produced for a cosmid or BAC data set. A difficulty with use of forward–reverse constraints in assembly is that some of the forward–reverse constraints are incorrect because of errors in lane tracking and cloning. Our strategy for dealing with this difficulty is based on the observation that a majority of the constraints are correct and wrong constraints usually occur randomly. Thus, a few unsatisfied constraints in a contig may not be sufficient to indicate an assembly error in the contig. However, if a sufficient number of constraints are all inconsistent with a join in a contig and all support an alternative join, it is likely that the current join is an error, and the alternative join should be made.
University of Tennessee1, Oak Ridge National Laboratory2, West Virginia University3, Umeå University4, University of British Columbia5, United States Department of Energy6, Ghent University7, Swedish University of Agricultural Sciences8, Institut national de la recherche agronomique9, Virginia Tech10, Michigan Technological University11, University of Toronto12, Pennsylvania State University13, University of Provence14, University of Georgia15, University of Florida16, University of California, Berkeley17, Lawrence Berkeley National Laboratory18, University of Arizona19, Purdue University20, Stanford University21, United States Department of Agriculture22, University of Turku23, University of Helsinki24, Massachusetts Institute of Technology25, University of Tennessee Health Science Center26, University of Tübingen27
TL;DR: The draft genome of the black cottonwood tree, Populus trichocarpa, has been reported in this paper, with more than 45,000 putative protein-coding genes identified.
Abstract: We report the draft genome of the black cottonwood tree, Populus trichocarpa. Integration of shotgun sequence assembly with genetic mapping enabled chromosome-scale reconstruction of the genome. More than 45,000 putative protein-coding genes were identified. Analysis of the assembled genome revealed a whole-genome duplication event; about 8000 pairs of duplicated genes from that event survived in the Populus genome. A second, older duplication event is indistinguishably coincident with the divergence of the Populus and Arabidopsis lineages. Nucleotide substitution, tandem gene duplication, and gross chromosomal rearrangement appear to proceed substantially more slowly in Populus than in Arabidopsis. Populus has more protein-coding genes than Arabidopsis, ranging on average from 1.4 to 1.6 putative Populus homologs for each Arabidopsis gene. However, the relative frequency of protein domains in the two genomes is similar. Overrepresented exceptions in Populus include genes associated with lignocellulosic wall biosynthesis, meristem development, disease resistance, and metabolite transport.
07 Jan 2008-Physical Review Letters
TL;DR: Measurements show that mobilities higher than 200 000 cm2/V s are achievable, if extrinsic disorder is eliminated and a sharp (thresholdlike) increase in resistivity observed above approximately 200 K is unexpected but can qualitatively be understood within a model of a rippled graphene sheet in which scattering occurs on intraripple flexural phonons.
Abstract: We have studied temperature dependences of electron transport in graphene and its bilayer and found extremely low electron-phonon scattering rates that set the fundamental limit on possible charge carrier mobilities at room temperature. Our measurements show that mobilities higher than 200 000 cm2/V s are achievable, if extrinsic disorder is eliminated. A sharp (thresholdlike) increase in resistivity observed above approximately 200 K is unexpected but can qualitatively be understood within a model of a rippled graphene sheet in which scattering occurs on intraripple flexural phonons.
24 Jul 2008-Nano Letters
TL;DR: The lithium storage properties of graphene nanosheet (GNS) materials as high capacity anode materials for rechargeable lithium secondary batteries (LIB) were investigated and the specific capacity of GNS was found to be 540 mAh/g, which is much larger than that of graphite, and this was increased by the incorporation of macromolecules of CNT and C60 to the GNS.
Abstract: The lithium storage properties of graphene nanosheet (GNS) materials as high capacity anode materials for rechargeable lithium secondary batteries (LIB) were investigated. Graphite is a practical anode material used for LIB, because of its capability for reversible lithium ion intercalation in the layered crystals, and the structural similarities of GNS to graphite may provide another type of intercalation anode compound. While the accommodation of lithium in these layered compounds is influenced by the layer spacing between the graphene nanosheets, control of the intergraphene sheet distance through interacting molecules such as carbon nanotubes (CNT) or fullerenes (C60) might be crucial for enhancement of the storage capacity. The specific capacity of GNS was found to be 540 mAh/g, which is much larger than that of graphite, and this was increased up to 730 mAh/g and 784 mAh/g, respectively, by the incorporation of macromolecules of CNT and C60 to the GNS.
TL;DR: An intermediate program representation, called the program dependence graph (PDG), that makes explicit both the data and control dependences for each operation in a program, allowing transformations to be triggered by one another and applied only to affected dependences.
Abstract: In this paper we present an intermediate program representation, called the program dependence graph (PDG), that makes explicit both the data and control dependences for each operation in a program. Data dependences have been used to represent only the relevant data flow relationships of a program. Control dependences are introduced to analogously represent only the essential control flow relationships of a program. Control dependences are derived from the usual control flow graph. Many traditional optimizations operate more efficiently on the PDG. Since dependences in the PDG connect computationally related parts of the program, a single walk of these dependences is sufficient to perform many optimizations. The PDG allows transformations such as vectorization, that previously required special treatment of control dependence, to be performed in a manner that is uniform for both control and data dependences. Program transformations that require interaction of the two dependence types can also be easily handled with our representation. As an example, an incremental approach to modifying data dependences resulting from branch deletion or loop unrolling is introduced. The PDG supports incremental optimization, permitting transformations to be triggered by one another and applied only to affected dependences.
Showing all 8023 results
|Anil K. Jain||183||1016||192151|
|Marc W. Kirschner||162||457||102145|
|Nicholas J. Turro||104||1131||53827|
|Richard P. Novick||99||295||34542|
|Markus J. Buehler||95||609||33054|
|Martin L. Yarmush||91||702||34591|
|Patrick M. Schlievert||90||444||32037|
|Lonnie O. Ingram||88||316||22217|
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