7 research outputs found
Implementation of parallel algorithm for k-mer enrichment analysis of genomic sequences
The goal of this thesis was to implement a sequential algorithm that would
search for subsequences in a genome. To accelerate the execution time of this
algorithm we designed a parallel version and implemented the parallel version
on a graphics card. The sequential algorithm had to search for predefined
subsequences in a genome that was represented as a sequence of characters. It
had to calculate the frequencies of sequence occurrences and the frequencies of
interactions on predefined positions and on randomly modified positions in the
genome, for each subsequence. Based on these frequencies it had to identify
sequences that were more frequent on certain locations in a given genome. Based
on data about protein-RNA interactions on certain locations in the genome, and
based on the found character sequences, the algorithm had to calculate and
statistically evaluate the frequencies of interactions. The sequential
algorithm was implemented in the C programming language, while the
parallelization was implemented on the OpenCL architecture
Implementation of parallel algorithm for k-mer enrichment analysis of genomic sequences
The goal of this thesis was to implement a sequential algorithm that would
search for subsequences in a genome. To accelerate the execution time of this
algorithm we designed a parallel version and implemented the parallel version
on a graphics card. The sequential algorithm had to search for predefined
subsequences in a genome that was represented as a sequence of characters. It
had to calculate the frequencies of sequence occurrences and the frequencies of
interactions on predefined positions and on randomly modified positions in the
genome, for each subsequence. Based on these frequencies it had to identify
sequences that were more frequent on certain locations in a given genome. Based
on data about protein-RNA interactions on certain locations in the genome, and
based on the found character sequences, the algorithm had to calculate and
statistically evaluate the frequencies of interactions. The sequential
algorithm was implemented in the C programming language, while the
parallelization was implemented on the OpenCL architecture
Implementation of parallel algorithm for k-mer enrichment analysis of genomic sequences
Cilj diplomske naloge je bil implementirati sekvenÄni algoritem za iskanje
krajŔih zaporedij v genomih, ga pohitriti s paralelizacijo ter implementirati
paralelno verzijo na grafiÄni kartici. SekvenÄni algoritem je moral poiskati
krajÅ”a zaporedja znakov v danem zaporedju, ki predstavlja genom. IzraÄunati je
moral frekvence pojavitev zaporedij in pogostost interakcij na podanih
položajih ter na nakljuÄno premaknjenih položajih, za vsako krajÅ”e zaporedje
posebej. Na podlagi pojavitev je nato moral doloÄiti, katera krajÅ”a zaporedja
so za doloÄene položaje v genomu bolj znaÄilna. Na podlagi podatkov o
interakcijah med proteini in genomom na doloÄenih položajih, ter na podlagi
najdenih krajÅ”ih zaporedij znakov, je moral nato izraÄunati in statistiÄno
ovrednotiti pogostost pojavitve interakcij. SekvenÄni algoritem smo
implementirali v programskem jeziku C, paralelizacijo sekvenÄnega algoritma pa
smo izvedli na podlagi arhitekture OpenCL, ki omogoÄa implementacijo algoritmov
na grafiÄnih karticah.The goal of this thesis was to implement a sequential algorithm that would
search for subsequences in a genome. To accelerate the execution time of this
algorithm we designed a parallel version and implemented the parallel version
on a graphics card. The sequential algorithm had to search for predefined
subsequences in a genome that was represented as a sequence of characters. It
had to calculate the frequencies of sequence occurrences and the frequencies of
interactions on predefined positions and on randomly modified positions in the
genome, for each subsequence. Based on these frequencies it had to identify
sequences that were more frequent on certain locations in a given genome. Based
on data about protein-RNA interactions on certain locations in the genome, and
based on the found character sequences, the algorithm had to calculate and
statistically evaluate the frequencies of interactions. The sequential
algorithm was implemented in the C programming language, while the
parallelization was implemented on the OpenCL architecture
Implementation of parallel algorithm for k-mer enrichment analysis of genomic sequences
Cilj diplomske naloge je bil implementirati sekvenÄni algoritem za iskanje
krajŔih zaporedij v genomih, ga pohitriti s paralelizacijo ter implementirati
paralelno verzijo na grafiÄni kartici. SekvenÄni algoritem je moral poiskati
krajÅ”a zaporedja znakov v danem zaporedju, ki predstavlja genom. IzraÄunati je
moral frekvence pojavitev zaporedij in pogostost interakcij na podanih
položajih ter na nakljuÄno premaknjenih položajih, za vsako krajÅ”e zaporedje
posebej. Na podlagi pojavitev je nato moral doloÄiti, katera krajÅ”a zaporedja
so za doloÄene položaje v genomu bolj znaÄilna. Na podlagi podatkov o
interakcijah med proteini in genomom na doloÄenih položajih, ter na podlagi
najdenih krajÅ”ih zaporedij znakov, je moral nato izraÄunati in statistiÄno
ovrednotiti pogostost pojavitve interakcij. SekvenÄni algoritem smo
implementirali v programskem jeziku C, paralelizacijo sekvenÄnega algoritma pa
smo izvedli na podlagi arhitekture OpenCL, ki omogoÄa implementacijo algoritmov
na grafiÄnih karticah.The goal of this thesis was to implement a sequential algorithm that would
search for subsequences in a genome. To accelerate the execution time of this
algorithm we designed a parallel version and implemented the parallel version
on a graphics card. The sequential algorithm had to search for predefined
subsequences in a genome that was represented as a sequence of characters. It
had to calculate the frequencies of sequence occurrences and the frequencies of
interactions on predefined positions and on randomly modified positions in the
genome, for each subsequence. Based on these frequencies it had to identify
sequences that were more frequent on certain locations in a given genome. Based
on data about protein-RNA interactions on certain locations in the genome, and
based on the found character sequences, the algorithm had to calculate and
statistically evaluate the frequencies of interactions. The sequential
algorithm was implemented in the C programming language, while the
parallelization was implemented on the OpenCL architecture
Stability of erythrocyte-derived nanovesicles assessed by light scattering and electron microscopy
Extracellular vesicles (EVs) are gaining increasing amounts of attention due to their potential use in diagnostics and therapy, but the poor reproducibility of the studies that have been conducted on these structures hinders their breakthrough into routine practice. We believe that a better understanding of EVs stability and methods to control their integrity are the key to resolving this issue. In this work, erythrocyte EVs (hbEVs) were isolated by centrifugation from suspensions of human erythrocytes that had been aged in vitro. The isolate was characterised by scanning (SEM) and cryo-transmission electron microscopy (cryo-TEM), flow cytometry (FCM), dynamic/static light scattering (LS), protein electrophoresis, and UV-V spectrometry. The hbEVs were exposed to various conditions (pH (4ā10), osmolarity (50ā1000 mOsm/L), temperature (15ā60 Ā°C), and surfactant Triton X-100 (10ā500 Ī¼M)). Their stability was evaluated by LS by considering the hydrodynamic radius (R), intensity of scattered light (I), and the shape parameter (Ļ). The morphology of the hbEVs that had been stored in phosphate-buffered saline with citrate (PBSācitrate) at 4 Ā°C remained consistent for more than 6 months. A change in the media properties (50ā1000 mOsm/L, pH 4ā10) had no significant effect on the R (=100ā130 nm). At pH values below 6 and above 8, at temperatures above 45 Ā°C, and in the presence of Triton X-100, hbEVs degradation was indicated by a decrease in I of more than 20%. Due to the simple preparation, homogeneous morphology, and stability of hbEVs under a wide range of conditions, they are considered to be a suitable option for EV reference material
Autologous Platelet and Extracellular Vesicle-Rich Plasma as Therapeutic Fluid: A Review
The preparation of autologous platelet and extracellular vesicle-rich plasma (PVRP) has been explored in many medical fields with the aim to benefit from its healing potential. In parallel, efforts are being invested to understand the function and dynamics of PVRP that is complex in its composition and interactions. Some clinical evidence reveals beneficial effects of PVRP, while some report that there were no effects. To optimize the preparation methods, functions and mechanisms of PVRP, its constituents should be better understood. With the intention to promote further studies of autologous therapeutic PVRP, we performed a review on some topics regarding PVRP composition, harvesting, assessment and preservation, and also on clinical experience following PVRP application in humans and animals. Besides the acknowledged actions of platelets, leukocytes and different molecules, we focus on extracellular vesicles that were found abundant in PVRP
Autologous Platelet and Extracellular Vesicle-Rich Plasma as Therapeutic Fluid:A Review
The preparation of autologous platelet and extracellular vesicle-rich plasma (PVRP) has been explored in many medical fields with the aim to benefit from its healing potential. In parallel, efforts are being invested to understand the function and dynamics of PVRP that is complex in its composition and interactions. Some clinical evidence reveals beneficial effects of PVRP, while some report that there were no effects. To optimize the preparation methods, functions and mechanisms of PVRP, its constituents should be better understood. With the intention to promote further studies of autologous therapeutic PVRP, we performed a review on some topics regarding PVRP composition, harvesting, assessment and preservation, and also on clinical experience following PVRP application in humans and animals. Besides the acknowledged actions of platelets, leukocytes and different molecules, we focus on extracellular vesicles that were found abundant in PVRP.</p