Knowledge about characteristics shared across known members of a protein family enables their identification within the complete set of proteins in an organism. Shared features are usually expressed through motifs, wh...
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Knowledge about characteristics shared across known members of a protein family enables their identification within the complete set of proteins in an organism. Shared features are usually expressed through motifs, which can incorporate specific patterns and even amino acid (AA) biases. Based on a set of classification patterns and biases it can be determined which additional proteins may belong to a specific family and share its functionality. A bioinformatics tool (Prot-Class) was implemented to examine protein sequences and characterize them based upon user-defined AA composition percentages and user defined AA patterns. In addition the tool allows for the identification of repeated AA patterns, biased AA compositions within windows of user-defined length, and the characteristics of putative signal peptides and glycosylphosphatidylinositol (GPI) lipid anchors. ProtClass is general purpose and can be applied to analyze protein sequences from any organism. The Prot-Class source code is available through the GNU General Public License v3 and can be accessed via the Google Code Repository: http://***/p/prot-class/.
Chromosomal aberrations and somatic mutations constitute key elements of the pathogenesis of myelodysplastic syndromes (MDS), a clonal hematologic malignancy characterized by cytopenias, a dysplastic bone marrow and p...
Chromosomal aberrations and somatic mutations constitute key elements of the pathogenesis of myelodysplastic syndromes (MDS), a clonal hematologic malignancy characterized by cytopenias, a dysplastic bone marrow and propensity to clonal evolution. Next generation sequencing (NGS) enables definition of somatic mutational patterns and clonal architecture as a discovery platform, and for clinical *** systematically applied NGS to 707 cases of MDS and MDS-related disorders. 205 cases (low-risk MDS: N=78, high-risk MDS: N=42, MDS/MPN: N=48 and sAML: N=37) were tested by whole exome sequencing (WES). For validation in an additional 502 patients (low-risk MDS: N=192, high-risk MDS: N=104, MDS/MPN: N=111 and sAML: N=95), targeted deep NGS was applied for 60 index genes which were most commonly affected in the cohort analyzed by WES. For NGS data analysis a statistical pipeline was developed to focus on: i) identification of the most relevant somatic mutations, and ii) minimization of false positive results. We studied serial samples from 21 exemplary informative patients. We also compared somatic mutational patterns to those seen in primary AML TCGA cohort (N=201). Given the size of the cohort, there was, for example, a 87% chance of seeing mutations at a frequency of 1% and a 98% of seeing those with a frequency of 2%. While focusing on the most common events, we observed 1117 somatic mutations in 199 genes. The 88 genes mutated mutated in >1% of cases with MDS carried 388 mutations in MDS+sAML (2.5/case), 128 in MDS/MPN (2.7/case) and 398 in pAML (2.0/case). The average number of mutations per case increased during progression (2.2 in lower-risk, 2.8 in higher-risk MDS, 3.4 in sAML). In MDS, the 30 most frequently affected genes were present at least once in 70% of patients. The 30 most frequently mutated genes in MDS/MPN were mutated in 82% of patients. Individual mutations were also sub-grouped according to their function. When we compared three MDS subcateg
The quantity of information on nanomaterial properties and behavior continues to grow rapidly. Without a concerted effort to collect, organize and mine disparate information coming out of current research efforts, the...
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This paper evaluates existing taxonomies aimed at characterizing the interaction between robots and their users and modifies them for health care applications. The modifications are based on existing robot technologie...
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ISBN:
(纸本)9781424441198
This paper evaluates existing taxonomies aimed at characterizing the interaction between robots and their users and modifies them for health care applications. The modifications are based on existing robot technologies and user acceptance of robotics. Characterization of the user, or in this case the patient, is a primary focus of the paper, as they present a unique new role as robot users. While therapeutic and monitoring-related applications for robots are still relatively uncommon, we believe they will begin to grow and thus it isimportant that the spurring relationship between robot and patient is well understood.
Effective execution of a planned path by an underwater vehicle is important for proper analysis of the gathered science data, as well as to ensure the safety of the vehicle during the mission. Here, we propose the use...
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Effective execution of a planned path by an underwater vehicle is important for proper analysis of the gathered science data, as well as to ensure the safety of the vehicle during the mission. Here, we propose the use of an unscented Kalman filter to aid in determining how the planned mission is executed. Given a set of waypoints that define a planned path and a dicretization of the ocean currents from a regional ocean model, we present an approach to determine the time interval at which the glider should surface to maintain a prescribed tracking error, while also limiting its time on the ocean surface. We assume practical mission parameters provided from previous field trials for the problem set up, and provide the simulated results of the Kalman filter mission planning approach. The results are initially compared to data from prior field experiments in which an autonomous glider executed the same path without pre-planning. Then, the results are validated through field trials with multiple autonomous gliders implementing different surfacing intervals simultaneously while following the same path.
We present a self-contained portable USB based device that can amplify and record small bioelectric signals from insects and animals. The system combines a purpose built low noise amplifier with off the shelf componen...
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ISBN:
(纸本)9781424441198
We present a self-contained portable USB based device that can amplify and record small bioelectric signals from insects and animals. The system combines a purpose built low noise amplifier with off the shelf components to provide a low cost low power system for recording electrophysiological signals. Using open source software the system is programmed as a simple USB device and can be connected to any USB capable computer for recording data. This simple and universal interface provides the ability to connect to a variety of systems. Open source acquisition software was also written to record signals under the linux operating system. Performance analysis shows that our device is able to record good quality signals both indoors and outdoors and delivers this performance at a very low cost. Compared to larger systems our device provides the additional advantage of portability given that it can fit into a pocket and costs a fraction of large systems used in electrophysiology labs.
Background: Diet is a critical element of diabetes self-management. An emerging area of research is the use of images for dietary records using mobile telephones with embedded cameras. These tools are being designed t...
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Micro Aerial Vehicles (MAVs) have gained a significant amount of research lately, with a number of universities and industry sponsors paving the way with micro flying robots to perform Intelligence, Surveillance and R...
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We present the hardware design, software architecture, and core algorithms of Herb 2.0, a bimanual mobile manipulator developed at the Personal robotics Lab at Carnegie Mellon University, Pittsburgh, PA. We have devel...
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An ideal haptic device should transmit a wide range of stable virtual model impedances (Z-width) with high transparency. Magneto-rheological fluid (MR) brakes are advantageous in haptic devices since they are passive ...
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An ideal haptic device should transmit a wide range of stable virtual model impedances (Z-width) with high transparency. Magneto-rheological fluid (MR) brakes are advantageous in haptic devices since they are passive actuators. However, they cannot provide high transparency and smooth interaction due to high viscous friction, residual torque, slow response, sticking and hysteresis effects. On the other hand, active actuators cannot simulate high virtual impedances stably, but provide high transparency with a closed loop control algorithm. In the proposed hybrid actuation a task divider control (TDC) algorithm was developed for torque sharing between two actuators to provide a large Z-width and improve both transparency and smoothness. The algorithm employs two parameters which were estimated experimentally and extended to entire achievable impedance range by artificial neural network (ANN) and curve fitting techniques. A 1-DOF device having an excitation motor at the user side and brushless DC motor and MR-brake in the haptic side was used in the experiments. The excitation motor is used to generate a white noise torque input to simulate a user for frequency domain transparency tests. Results of the proposed and conventional closed loop impedance control (CLIC) algorithms were compared. The proposed algorithm improves the transparency of MR-brake by eliminating its drawbacks and presents a larger Z-width than the active actuator alone.
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