The Experts below are selected from a list of 264 Experts worldwide ranked by ideXlab platform
Joanna I. Sulkowska - One of the best experts on this subject based on the ideXlab platform.
-
GLN: a method to reveal unique properties of lasso type topology in proteins
Scientific Reports, 2020Co-Authors: Wanda Niemyska, Kenneth C. Millett, Joanna I. SulkowskaAbstract:Geometry and topology are the main factors that determine the functional properties of proteins. In this work, we show how to use the Gauss linking integral (GLN) in the form of a Matrix Diagram—for a pair of a loop and a tail—to study both the geometry and topology of proteins with closed loops e.g. lassos. We show that the GLN method is a significantly faster technique to detect entanglement in lasso proteins in comparison with other methods. Based on the GLN technique, we conduct comprehensive analysis of all proteins deposited in the PDB and compare it to the statistical properties of the polymers. We show how high and low GLN values correlate with the internal exibility of proteins, and how the GLN in the form of a Matrix Diagram can be used to study folding and unfolding routes. Finally, we discuss how the GLN method can be applied to study entanglement between two structures none of which are closed loops. Since this approach is much faster than other linking invariants, the next step will be evaluation of lassos in much longer molecules such as RNA or loops in a single chromosome.
-
GLN -- a method to reveal unique properties of lasso type topology in proteins
arXiv: Biomolecules, 2020Co-Authors: Wanda Niemyska, Kenneth C. Millett, Joanna I. SulkowskaAbstract:Geometry and topology are the main factors that determine the functional properties of proteins. In this work, we show how to use the Gauss linking integral (GLN) in the form of a Matrix Diagram - for a pair of a loop and a tail - to study both the geometry and topology of proteins with closed loops e.g. lassos. We show that the GLN method is a significantly faster technique to detect entanglement in lasso proteins in comparison with other methods. Based on the GLN technique, we conduct comprehensive analysis of all proteins deposited in the PDB and compare it to the statistical properties of the polymers. We found that there are significantly more lassos with negative crossings than those with positive ones in proteins, the average value of maxGLN (maximal GLN between loop and pieces of tail) depends logarithmically on the length of a tail similarly as in the polymers. Next, we show the how high and low GLN values correlate with the internal exibility of proteins, and how the GLN in the form of a Matrix Diagram can be used to study folding and unfolding routes. Finally, we discuss how the GLN method can be applied to study entanglement between two structures none of which are closed loops. Since this approach is much faster than other linking invariants, the next step will be evaluation of lassos in much longer molecules such as RNA or loops in a single chromosome.
-
Genus for biomolecules.
Nucleic acids research, 2019Co-Authors: Pawel Rubach, Joanna I. Sulkowska, Sebastian Zajac, Borys Jastrzębski, Piotr SułkowskiAbstract:The 'Genus for biomolecules' database (http://genus.fuw.edu.pl) collects information about topological structure and complexity of proteins and RNA chains, which is captured by the genus of a given chain and its subchains. For each biomolecule, this information is shown in the form of a genus trace plot, as well as a genus Matrix Diagram. We assemble such information for all and RNA structures deposited in the Protein Data Bank (PDB). This database presents also various statistics and extensive information about the biological function of the analyzed biomolecules. The database is regularly self-updating, once new structures are deposited in the PDB. Moreover, users can analyze their own structures.
-
KnotGenome: a server to analyze entanglements of chromosomes.
Nucleic acids research, 2018Co-Authors: Joanna I. Sulkowska, Szymon Niewieczerzal, Aleksandra I. Jarmolinska, Jonathan Tammo Siebert, Peter Virnau, Wanda NiemyskaAbstract:The KnotGenome server enables the topological analysis of chromosome model data using three-dimensional coordinate files of chromosomes as input. In particular, it detects prime and composite knots in single chromosomes, and links between chromosomes. The knotting complexity of the chromosome is presented in the form of a Matrix Diagram that reveals the knot type of the entire polynucleotide chain and of each of its subchains. Links are determined by means of the Gaussian linking integral and the HOMFLY-PT polynomial. Entangled chromosomes are presented graphically in an intuitive way. It is also possible to relax structure with short molecular dynamics runs before the analysis. KnotGenome is freely available at http://knotgenom.cent.uw.edu.pl/.
-
KnotProt: a database of proteins with knots and slipknots
Nucleic Acids Research, 2014Co-Authors: Michal Jamroz, Wanda Niemyska, Kenneth C. Millett, Piotr Sułkowski, Eric J. Rawdon, Andrzej Stasiak, Joanna I. SulkowskaAbstract:The protein topology database KnotProt, http://knotprot.cent.uw.edu.pl/, collects information about protein structures with open polypeptide chains forming knots or slipknots. The knotting complexity of the cataloged proteins is presented in the form of a Matrix Diagram that shows users the knot type of the entire polypeptide chain and of each of its subchains. The pattern visible in the Matrix gives the knotting fingerprint of a given protein and permits users to determine, for example, the minimal length of the knotted regions (knot's core size) or the depth of a knot, i.e. how many amino acids can be removed from either end of the cataloged protein structure before converting it from a knot to a different type of knot. In addition, the database presents extensive information about the biological functions, families and fold types of proteins with non-trivial knotting. As an additional feature, the KnotProt database enables users to submit protein or polymer chains and generate their knotting fingerprints
Salem Derisavi - One of the best experts on this subject based on the ideXlab platform.
-
lumping Matrix Diagram representations of markov models
Dependable Systems and Networks, 2005Co-Authors: Salem Derisavi, Peter Kemper, William H SandersAbstract:Continuous-time Markov chains (CTMCs) have been used successfully to model the dependability and performability of many systems. Matrix Diagrams (MDs) are known to be a space-efficient, symbolic representation of large CTMCs. In this paper, we identify local conditions for exact and ordinary lumpings that allow us to lump MD representations of Markov models in a compositional manner. We propose a lumping algorithm for CTMCs that are represented as MDs that is based on partition refinement, is applied to each level of an MD directly, and results in an MD representation of the lumped CTMC. Our compositional lumping approach is complementary to other known model-level lumping approaches for Matrix Diagrams. The approach has been implemented, and we demonstrate its efficiency and benefits by evaluating an example model of a tandem multi-processor system with load balancing and failure and repair operations.
-
the mobius state level abstract functional interface
Lecture Notes in Computer Science, 2002Co-Authors: Salem Derisavi, Peter Kemper, William H Sanders, T CourtneyAbstract:A key advantage of the Mobius modeling environment is the ease with which one can incorporate new modeling formalisms, model composition and connection methods, and model solution methods. In this paper, we describe a new state-level abstract functional interface (AFI) for Mobius that allows numerical solution methods to communicate with Mobius state-level models via the abstraction of a labeled transition system. This abstraction, and its corresponding implementation as a set of containers and iterators, yields an important separation of concerns: It is possible to treat separately the problem of representing large labeled transition systems, like generator matrices of continuous-time Markov chains, and the problem of analyzing these systems. For example, any numerical solver (e.g., Jacobi, SOR, or uniformization) that accesses a model through the Mobius state-level AFI can operate on a variety of state-space representations, including "on-the-fly," disk-based, sparse-Matrix, Kronecker, and Matrix-Diagram representations, without requiring that the implementation be changed to match the state-space representation. This abstraction thus avoids redundant implementations of solvers and state-generation techniques, eases research cooperation, and simplifies comparison of approaches as well as benchmarking. In addition to providing a formal definition of the Mobius state-level AFI, we illustrate its use on two state-space representations (a sparse Matrix and a Kronecker representation) and two numerical solvers (Jacobi and SOR). With the help of this implementation and two example models, we demonstrate that the AFI provides the benefits of transparency while introducing only minor slowdowns in solution speed.
-
Computer Performance Evaluation / TOOLS - The Möbius State-Level Abstract Functional Interface
Computer Performance Evaluation: Modelling Techniques and Tools, 2002Co-Authors: Salem Derisavi, Peter Kemper, William H Sanders, T CourtneyAbstract:A key advantage of the Mobius modeling environment is the ease with which one can incorporate new modeling formalisms, model composition and connection methods, and model solution methods. In this paper, we describe a new state-level abstract functional interface (AFI) for Mobius that allows numerical solution methods to communicate with Mobius state-level models via the abstraction of a labeled transition system. This abstraction, and its corresponding implementation as a set of containers and iterators, yields an important separation of concerns: It is possible to treat separately the problem of representing large labeled transition systems, like generator matrices of continuous-time Markov chains, and the problem of analyzing these systems. For example, any numerical solver (e.g., Jacobi, SOR, or uniformization) that accesses a model through the Mobius state-level AFI can operate on a variety of state-space representations, including "on-the-fly," disk-based, sparse-Matrix, Kronecker, and Matrix-Diagram representations, without requiring that the implementation be changed to match the state-space representation. This abstraction thus avoids redundant implementations of solvers and state-generation techniques, eases research cooperation, and simplifies comparison of approaches as well as benchmarking. In addition to providing a formal definition of the Mobius state-level AFI, we illustrate its use on two state-space representations (a sparse Matrix and a Kronecker representation) and two numerical solvers (Jacobi and SOR). With the help of this implementation and two example models, we demonstrate that the AFI provides the benefits of transparency while introducing only minor slowdowns in solution speed.
-
DSN - Lumping Matrix Diagram representations of Markov models
2005 International Conference on Dependable Systems and Networks (DSN'05), 1Co-Authors: Salem Derisavi, Peter Kemper, William H SandersAbstract:Continuous-time Markov chains (CTMCs) have been used successfully to model the dependability and performability of many systems. Matrix Diagrams (MDs) are known to be a space-efficient, symbolic representation of large CTMCs. In this paper, we identify local conditions for exact and ordinary lumpings that allow us to lump MD representations of Markov models in a compositional manner. We propose a lumping algorithm for CTMCs that are represented as MDs that is based on partition refinement, is applied to each level of an MD directly, and results in an MD representation of the lumped CTMC. Our compositional lumping approach is complementary to other known model-level lumping approaches for Matrix Diagrams. The approach has been implemented, and we demonstrate its efficiency and benefits by evaluating an example model of a tandem multi-processor system with load balancing and failure and repair operations.
Wanda Niemyska - One of the best experts on this subject based on the ideXlab platform.
-
GLN: a method to reveal unique properties of lasso type topology in proteins
Scientific Reports, 2020Co-Authors: Wanda Niemyska, Kenneth C. Millett, Joanna I. SulkowskaAbstract:Geometry and topology are the main factors that determine the functional properties of proteins. In this work, we show how to use the Gauss linking integral (GLN) in the form of a Matrix Diagram—for a pair of a loop and a tail—to study both the geometry and topology of proteins with closed loops e.g. lassos. We show that the GLN method is a significantly faster technique to detect entanglement in lasso proteins in comparison with other methods. Based on the GLN technique, we conduct comprehensive analysis of all proteins deposited in the PDB and compare it to the statistical properties of the polymers. We show how high and low GLN values correlate with the internal exibility of proteins, and how the GLN in the form of a Matrix Diagram can be used to study folding and unfolding routes. Finally, we discuss how the GLN method can be applied to study entanglement between two structures none of which are closed loops. Since this approach is much faster than other linking invariants, the next step will be evaluation of lassos in much longer molecules such as RNA or loops in a single chromosome.
-
GLN -- a method to reveal unique properties of lasso type topology in proteins
arXiv: Biomolecules, 2020Co-Authors: Wanda Niemyska, Kenneth C. Millett, Joanna I. SulkowskaAbstract:Geometry and topology are the main factors that determine the functional properties of proteins. In this work, we show how to use the Gauss linking integral (GLN) in the form of a Matrix Diagram - for a pair of a loop and a tail - to study both the geometry and topology of proteins with closed loops e.g. lassos. We show that the GLN method is a significantly faster technique to detect entanglement in lasso proteins in comparison with other methods. Based on the GLN technique, we conduct comprehensive analysis of all proteins deposited in the PDB and compare it to the statistical properties of the polymers. We found that there are significantly more lassos with negative crossings than those with positive ones in proteins, the average value of maxGLN (maximal GLN between loop and pieces of tail) depends logarithmically on the length of a tail similarly as in the polymers. Next, we show the how high and low GLN values correlate with the internal exibility of proteins, and how the GLN in the form of a Matrix Diagram can be used to study folding and unfolding routes. Finally, we discuss how the GLN method can be applied to study entanglement between two structures none of which are closed loops. Since this approach is much faster than other linking invariants, the next step will be evaluation of lassos in much longer molecules such as RNA or loops in a single chromosome.
-
KnotGenome: a server to analyze entanglements of chromosomes.
Nucleic acids research, 2018Co-Authors: Joanna I. Sulkowska, Szymon Niewieczerzal, Aleksandra I. Jarmolinska, Jonathan Tammo Siebert, Peter Virnau, Wanda NiemyskaAbstract:The KnotGenome server enables the topological analysis of chromosome model data using three-dimensional coordinate files of chromosomes as input. In particular, it detects prime and composite knots in single chromosomes, and links between chromosomes. The knotting complexity of the chromosome is presented in the form of a Matrix Diagram that reveals the knot type of the entire polynucleotide chain and of each of its subchains. Links are determined by means of the Gaussian linking integral and the HOMFLY-PT polynomial. Entangled chromosomes are presented graphically in an intuitive way. It is also possible to relax structure with short molecular dynamics runs before the analysis. KnotGenome is freely available at http://knotgenom.cent.uw.edu.pl/.
-
KnotProt: a database of proteins with knots and slipknots
Nucleic Acids Research, 2014Co-Authors: Michal Jamroz, Wanda Niemyska, Kenneth C. Millett, Piotr Sułkowski, Eric J. Rawdon, Andrzej Stasiak, Joanna I. SulkowskaAbstract:The protein topology database KnotProt, http://knotprot.cent.uw.edu.pl/, collects information about protein structures with open polypeptide chains forming knots or slipknots. The knotting complexity of the cataloged proteins is presented in the form of a Matrix Diagram that shows users the knot type of the entire polypeptide chain and of each of its subchains. The pattern visible in the Matrix gives the knotting fingerprint of a given protein and permits users to determine, for example, the minimal length of the knotted regions (knot's core size) or the depth of a knot, i.e. how many amino acids can be removed from either end of the cataloged protein structure before converting it from a knot to a different type of knot. In addition, the database presents extensive information about the biological functions, families and fold types of proteins with non-trivial knotting. As an additional feature, the KnotProt database enables users to submit protein or polymer chains and generate their knotting fingerprints
William H Sanders - One of the best experts on this subject based on the ideXlab platform.
-
lumping Matrix Diagram representations of markov models
Dependable Systems and Networks, 2005Co-Authors: Salem Derisavi, Peter Kemper, William H SandersAbstract:Continuous-time Markov chains (CTMCs) have been used successfully to model the dependability and performability of many systems. Matrix Diagrams (MDs) are known to be a space-efficient, symbolic representation of large CTMCs. In this paper, we identify local conditions for exact and ordinary lumpings that allow us to lump MD representations of Markov models in a compositional manner. We propose a lumping algorithm for CTMCs that are represented as MDs that is based on partition refinement, is applied to each level of an MD directly, and results in an MD representation of the lumped CTMC. Our compositional lumping approach is complementary to other known model-level lumping approaches for Matrix Diagrams. The approach has been implemented, and we demonstrate its efficiency and benefits by evaluating an example model of a tandem multi-processor system with load balancing and failure and repair operations.
-
the mobius state level abstract functional interface
Lecture Notes in Computer Science, 2002Co-Authors: Salem Derisavi, Peter Kemper, William H Sanders, T CourtneyAbstract:A key advantage of the Mobius modeling environment is the ease with which one can incorporate new modeling formalisms, model composition and connection methods, and model solution methods. In this paper, we describe a new state-level abstract functional interface (AFI) for Mobius that allows numerical solution methods to communicate with Mobius state-level models via the abstraction of a labeled transition system. This abstraction, and its corresponding implementation as a set of containers and iterators, yields an important separation of concerns: It is possible to treat separately the problem of representing large labeled transition systems, like generator matrices of continuous-time Markov chains, and the problem of analyzing these systems. For example, any numerical solver (e.g., Jacobi, SOR, or uniformization) that accesses a model through the Mobius state-level AFI can operate on a variety of state-space representations, including "on-the-fly," disk-based, sparse-Matrix, Kronecker, and Matrix-Diagram representations, without requiring that the implementation be changed to match the state-space representation. This abstraction thus avoids redundant implementations of solvers and state-generation techniques, eases research cooperation, and simplifies comparison of approaches as well as benchmarking. In addition to providing a formal definition of the Mobius state-level AFI, we illustrate its use on two state-space representations (a sparse Matrix and a Kronecker representation) and two numerical solvers (Jacobi and SOR). With the help of this implementation and two example models, we demonstrate that the AFI provides the benefits of transparency while introducing only minor slowdowns in solution speed.
-
Computer Performance Evaluation / TOOLS - The Möbius State-Level Abstract Functional Interface
Computer Performance Evaluation: Modelling Techniques and Tools, 2002Co-Authors: Salem Derisavi, Peter Kemper, William H Sanders, T CourtneyAbstract:A key advantage of the Mobius modeling environment is the ease with which one can incorporate new modeling formalisms, model composition and connection methods, and model solution methods. In this paper, we describe a new state-level abstract functional interface (AFI) for Mobius that allows numerical solution methods to communicate with Mobius state-level models via the abstraction of a labeled transition system. This abstraction, and its corresponding implementation as a set of containers and iterators, yields an important separation of concerns: It is possible to treat separately the problem of representing large labeled transition systems, like generator matrices of continuous-time Markov chains, and the problem of analyzing these systems. For example, any numerical solver (e.g., Jacobi, SOR, or uniformization) that accesses a model through the Mobius state-level AFI can operate on a variety of state-space representations, including "on-the-fly," disk-based, sparse-Matrix, Kronecker, and Matrix-Diagram representations, without requiring that the implementation be changed to match the state-space representation. This abstraction thus avoids redundant implementations of solvers and state-generation techniques, eases research cooperation, and simplifies comparison of approaches as well as benchmarking. In addition to providing a formal definition of the Mobius state-level AFI, we illustrate its use on two state-space representations (a sparse Matrix and a Kronecker representation) and two numerical solvers (Jacobi and SOR). With the help of this implementation and two example models, we demonstrate that the AFI provides the benefits of transparency while introducing only minor slowdowns in solution speed.
-
DSN - Lumping Matrix Diagram representations of Markov models
2005 International Conference on Dependable Systems and Networks (DSN'05), 1Co-Authors: Salem Derisavi, Peter Kemper, William H SandersAbstract:Continuous-time Markov chains (CTMCs) have been used successfully to model the dependability and performability of many systems. Matrix Diagrams (MDs) are known to be a space-efficient, symbolic representation of large CTMCs. In this paper, we identify local conditions for exact and ordinary lumpings that allow us to lump MD representations of Markov models in a compositional manner. We propose a lumping algorithm for CTMCs that are represented as MDs that is based on partition refinement, is applied to each level of an MD directly, and results in an MD representation of the lumped CTMC. Our compositional lumping approach is complementary to other known model-level lumping approaches for Matrix Diagrams. The approach has been implemented, and we demonstrate its efficiency and benefits by evaluating an example model of a tandem multi-processor system with load balancing and failure and repair operations.
T Courtney - One of the best experts on this subject based on the ideXlab platform.
-
the mobius state level abstract functional interface
Lecture Notes in Computer Science, 2002Co-Authors: Salem Derisavi, Peter Kemper, William H Sanders, T CourtneyAbstract:A key advantage of the Mobius modeling environment is the ease with which one can incorporate new modeling formalisms, model composition and connection methods, and model solution methods. In this paper, we describe a new state-level abstract functional interface (AFI) for Mobius that allows numerical solution methods to communicate with Mobius state-level models via the abstraction of a labeled transition system. This abstraction, and its corresponding implementation as a set of containers and iterators, yields an important separation of concerns: It is possible to treat separately the problem of representing large labeled transition systems, like generator matrices of continuous-time Markov chains, and the problem of analyzing these systems. For example, any numerical solver (e.g., Jacobi, SOR, or uniformization) that accesses a model through the Mobius state-level AFI can operate on a variety of state-space representations, including "on-the-fly," disk-based, sparse-Matrix, Kronecker, and Matrix-Diagram representations, without requiring that the implementation be changed to match the state-space representation. This abstraction thus avoids redundant implementations of solvers and state-generation techniques, eases research cooperation, and simplifies comparison of approaches as well as benchmarking. In addition to providing a formal definition of the Mobius state-level AFI, we illustrate its use on two state-space representations (a sparse Matrix and a Kronecker representation) and two numerical solvers (Jacobi and SOR). With the help of this implementation and two example models, we demonstrate that the AFI provides the benefits of transparency while introducing only minor slowdowns in solution speed.
-
Computer Performance Evaluation / TOOLS - The Möbius State-Level Abstract Functional Interface
Computer Performance Evaluation: Modelling Techniques and Tools, 2002Co-Authors: Salem Derisavi, Peter Kemper, William H Sanders, T CourtneyAbstract:A key advantage of the Mobius modeling environment is the ease with which one can incorporate new modeling formalisms, model composition and connection methods, and model solution methods. In this paper, we describe a new state-level abstract functional interface (AFI) for Mobius that allows numerical solution methods to communicate with Mobius state-level models via the abstraction of a labeled transition system. This abstraction, and its corresponding implementation as a set of containers and iterators, yields an important separation of concerns: It is possible to treat separately the problem of representing large labeled transition systems, like generator matrices of continuous-time Markov chains, and the problem of analyzing these systems. For example, any numerical solver (e.g., Jacobi, SOR, or uniformization) that accesses a model through the Mobius state-level AFI can operate on a variety of state-space representations, including "on-the-fly," disk-based, sparse-Matrix, Kronecker, and Matrix-Diagram representations, without requiring that the implementation be changed to match the state-space representation. This abstraction thus avoids redundant implementations of solvers and state-generation techniques, eases research cooperation, and simplifies comparison of approaches as well as benchmarking. In addition to providing a formal definition of the Mobius state-level AFI, we illustrate its use on two state-space representations (a sparse Matrix and a Kronecker representation) and two numerical solvers (Jacobi and SOR). With the help of this implementation and two example models, we demonstrate that the AFI provides the benefits of transparency while introducing only minor slowdowns in solution speed.