The Experts below are selected from a list of 58788 Experts worldwide ranked by ideXlab platform
Ilya J Finkelstein - One of the best experts on this subject based on the ideXlab platform.
-
massively Parallel kinetic profiling of natural and engineered crispr nucleases
Biophysical Journal, 2021Co-Authors: Stephen K Jones, John A Hawkins, Nicole V Johnson, Cheulhee Jung, James R Rybarski, Janice S Chen, Jennifer A Doudna, William H Press, Ilya J FinkelsteinAbstract:Abstract Engineered Streptococcus pyogenes (Sp) Cas9s and Acidaminococcus sp. (As) Cas12a (formerly Cpf1) improve cleavage specificity in human cells. However, the fidelity, enzymatic mechanisms, and cleavage products of emerging CRISPR nucleases have not been profiled systematically across partially mispaired off-target DNA sequences. Here, we describe NucleaSeq— nuclease digestion and deep sequencing—a massively Parallel Platform that measures cleavage kinetics and captures the time-resolved identities of cleaved products for more than ten thousand DNA targets that include mismatches, insertions, and deletions relative to the guide RNA. The binding specificity of each enzyme is measured on the same DNA library via the chip-hybridized association mapping Platform (CHAMP). Using this integrated cleavage and binding Platform, we profile four SpCas9 variants and AsCas12a. Engineered Cas9s retain wtCas9-like off-target binding but increase cleavage specificity; Cas9-HF1 shows the most dramatic increase in cleavage specificity. Surprisingly, wtCas12a—reported as a more specific nuclease in cells—has cleavage specificity similar to wtCas9 in vitro. Initial cleavage position and subsequent end-trimming vary across nucleases, guide RNA sequences, and position and base identity of mispairs in target DNAs. Using these large datasets, we develop a biophysical model that reveals mechanistic insights into off-target cleavage activities by these nucleases. More broadly, NucleaSeq enables rapid, quantitative, and systematic comparison of the specificities and cleavage products of engineered and natural nucleases.
-
massively Parallel kinetic profiling of natural and engineered crispr nucleases
Nature Biotechnology, 2021Co-Authors: Stephen K Jones, John A Hawkins, Nicole V Johnson, Cheulhee Jung, James R Rybarski, Janice S Chen, Jennifer A Doudna, William H Press, Ilya J FinkelsteinAbstract:Engineered SpCas9s and AsCas12a cleave fewer off-target genomic sites than wild-type (wt) Cas9. However, understanding their fidelity, mechanisms and cleavage outcomes requires systematic profiling across mispaired target DNAs. Here we describe NucleaSeq-nuclease digestion and deep sequencing-a massively Parallel Platform that measures the cleavage kinetics and time-resolved cleavage products for over 10,000 targets containing mismatches, insertions and deletions relative to the guide RNA. Combining cleavage rates and binding specificities on the same target libraries, we benchmarked five SpCas9 variants and AsCas12a. A biophysical model built from these data sets revealed mechanistic insights into off-target cleavage. Engineered Cas9s, especially Cas9-HF1, dramatically increased cleavage specificity but not binding specificity compared to wtCas9. Surprisingly, AsCas12a cleavage specificity differed little from that of wtCas9. Initial DNA cleavage sites and end trimming varied by nuclease, guide RNA and the positions of mispaired nucleotides. More broadly, NucleaSeq enables rapid, quantitative and systematic comparisons of specificity and cleavage outcomes across engineered and natural nucleases.
Erven Rohou - One of the best experts on this subject based on the ideXlab platform.
-
towards automatic binary runtime loop de Parallelization using on stack replacement
Information Processing Letters, 2019Co-Authors: Marwa Yusuf, Ahmed Elmahdy, Erven RohouAbstract:Abstract Runtime compilation has opportunities to Parallelize code which are generally not available using static Parallelization approaches. However, the Parallelized code can possibly slowdown the performance due to unforeseen Parallel overheads such as synchronization and speculation support pertaining to the chosen Parallelization strategy and the underlying Parallel Platform. Moreover, with the wide usage of heterogeneous architectures, such choice options become more pronounced. In this paper, we consider an adaptive form of the Parallelization operation, for the first time. We propose a method for performing on-stack de-Parallelization for a Parallelized binary loop at runtime, thereby allowing for rapid loop replacement with a more optimized one. For this paper, we consider a loop Parallelization strategy and propose a corresponding de-Parallelization method. The method relies on stopping the execution at safe points, gathering threads' states, producing a corresponding serial code, and continuing execution serially. The decision to de-Parallelize or not is taken based on the anticipated speedup. To assess the extent of our approach, we have conducted an initial study on a small set of programs with various Parallelization overheads. Results show up to 4× performance improvement for a synchronization intense program on a 4-core Intel processor.
Clement Gosselin - One of the best experts on this subject based on the ideXlab platform.
-
workspace analysis and optimal design of a 3 leg 6 dof Parallel Platform mechanism
International Conference on Robotics and Automation, 2003Co-Authors: Bruno Monsarrat, Clement GosselinAbstract:A new class of six-degree-of-freedom (DOFs) spatial Parallel Platform mechanism is considered in this paper. The architecture consists of a mobile Platform connected to the base by three identical kinematic chains using five-bar linkages. Recent investigations showed that Parallel mechanisms with such a topology for the legs can be efficiently statically balanced using only light elastic elements. This paper follows up with a workspace analysis and optimization of the design of that Parallel mechanism. More specifically, considering a possible industrial application of the architecture as a positioning and orienting device of heavy loads, an optimization procedure for the maximization of the volume of the three-dimensional (3-D) constant-orientation workspace of the mechanism is first presented. As the mechanism could also have great potential as a motion base for flight simulators, we develop here a discretization method for the computation and graphical representation of a new workspace with coupled translational and rotational DOFs. This workspace can be defined as the 3-D space which can be obtained when generalized coordinates x,y and torsion angle /spl psi/ in the tilt-and-torsion angles parametrization are constant. A second procedure is then presented for the maximization of the volume of this second subset of the complete workspace. For both approaches, our purpose is to attempt an optimal design of the mechanism by maximizing the volume of the associated 3-D Cartesian region that is free of critical singularity loci.
-
singularity analysis of a three leg six degree of freedom Parallel Platform mechanism based on grassmann line geometry
The International Journal of Robotics Research, 2001Co-Authors: Bruno Monsarrat, Clement GosselinAbstract:This paper addresses the determination of the singularity loci of a six-degree-of-freedom spatial Parallel Platform mechanism of a new type that can be statically balanced. The mechanism consists of a base and a mobile Platform that are connected by three legs using five-bar linkages. A general formulation of the Jacobian matrix is first derived that allows one to determine the Plucker vectors associated with the six input angles of the architecture. The linear dependencies between the corresponding lines are studied using Grassmann line geometry, and the singular configurations are presented using simple geometric rules. It is shown that most of the singular configurations of the three-leg six-degree-of-freedom Parallel manipulator can be reduced to the generation of a general linear complex. Expressions describing all the corresponding singularities are then obtained in closed form. Thus, it is shown that for a given orientation of the mobile Platform, the singularity locus corresponding to the general ...
Stephen K Jones - One of the best experts on this subject based on the ideXlab platform.
-
massively Parallel kinetic profiling of natural and engineered crispr nucleases
Biophysical Journal, 2021Co-Authors: Stephen K Jones, John A Hawkins, Nicole V Johnson, Cheulhee Jung, James R Rybarski, Janice S Chen, Jennifer A Doudna, William H Press, Ilya J FinkelsteinAbstract:Abstract Engineered Streptococcus pyogenes (Sp) Cas9s and Acidaminococcus sp. (As) Cas12a (formerly Cpf1) improve cleavage specificity in human cells. However, the fidelity, enzymatic mechanisms, and cleavage products of emerging CRISPR nucleases have not been profiled systematically across partially mispaired off-target DNA sequences. Here, we describe NucleaSeq— nuclease digestion and deep sequencing—a massively Parallel Platform that measures cleavage kinetics and captures the time-resolved identities of cleaved products for more than ten thousand DNA targets that include mismatches, insertions, and deletions relative to the guide RNA. The binding specificity of each enzyme is measured on the same DNA library via the chip-hybridized association mapping Platform (CHAMP). Using this integrated cleavage and binding Platform, we profile four SpCas9 variants and AsCas12a. Engineered Cas9s retain wtCas9-like off-target binding but increase cleavage specificity; Cas9-HF1 shows the most dramatic increase in cleavage specificity. Surprisingly, wtCas12a—reported as a more specific nuclease in cells—has cleavage specificity similar to wtCas9 in vitro. Initial cleavage position and subsequent end-trimming vary across nucleases, guide RNA sequences, and position and base identity of mispairs in target DNAs. Using these large datasets, we develop a biophysical model that reveals mechanistic insights into off-target cleavage activities by these nucleases. More broadly, NucleaSeq enables rapid, quantitative, and systematic comparison of the specificities and cleavage products of engineered and natural nucleases.
-
massively Parallel kinetic profiling of natural and engineered crispr nucleases
Nature Biotechnology, 2021Co-Authors: Stephen K Jones, John A Hawkins, Nicole V Johnson, Cheulhee Jung, James R Rybarski, Janice S Chen, Jennifer A Doudna, William H Press, Ilya J FinkelsteinAbstract:Engineered SpCas9s and AsCas12a cleave fewer off-target genomic sites than wild-type (wt) Cas9. However, understanding their fidelity, mechanisms and cleavage outcomes requires systematic profiling across mispaired target DNAs. Here we describe NucleaSeq-nuclease digestion and deep sequencing-a massively Parallel Platform that measures the cleavage kinetics and time-resolved cleavage products for over 10,000 targets containing mismatches, insertions and deletions relative to the guide RNA. Combining cleavage rates and binding specificities on the same target libraries, we benchmarked five SpCas9 variants and AsCas12a. A biophysical model built from these data sets revealed mechanistic insights into off-target cleavage. Engineered Cas9s, especially Cas9-HF1, dramatically increased cleavage specificity but not binding specificity compared to wtCas9. Surprisingly, AsCas12a cleavage specificity differed little from that of wtCas9. Initial DNA cleavage sites and end trimming varied by nuclease, guide RNA and the positions of mispaired nucleotides. More broadly, NucleaSeq enables rapid, quantitative and systematic comparisons of specificity and cleavage outcomes across engineered and natural nucleases.
Marwa Yusuf - One of the best experts on this subject based on the ideXlab platform.
-
towards automatic binary runtime loop de Parallelization using on stack replacement
Information Processing Letters, 2019Co-Authors: Marwa Yusuf, Ahmed Elmahdy, Erven RohouAbstract:Abstract Runtime compilation has opportunities to Parallelize code which are generally not available using static Parallelization approaches. However, the Parallelized code can possibly slowdown the performance due to unforeseen Parallel overheads such as synchronization and speculation support pertaining to the chosen Parallelization strategy and the underlying Parallel Platform. Moreover, with the wide usage of heterogeneous architectures, such choice options become more pronounced. In this paper, we consider an adaptive form of the Parallelization operation, for the first time. We propose a method for performing on-stack de-Parallelization for a Parallelized binary loop at runtime, thereby allowing for rapid loop replacement with a more optimized one. For this paper, we consider a loop Parallelization strategy and propose a corresponding de-Parallelization method. The method relies on stopping the execution at safe points, gathering threads' states, producing a corresponding serial code, and continuing execution serially. The decision to de-Parallelize or not is taken based on the anticipated speedup. To assess the extent of our approach, we have conducted an initial study on a small set of programs with various Parallelization overheads. Results show up to 4× performance improvement for a synchronization intense program on a 4-core Intel processor.
