61 research outputs found
Comparative analysis of an experimental subcellular protein localization assay and in silico prediction methods
The subcellular localization of a protein can provide important information about its function within the cell. As eukaryotic cells and particularly mammalian cells are characterized by a high degree of compartmentalization, most protein activities can be assigned to particular cellular compartments. The categorization of proteins by their subcellular localization is therefore one of the essential goals of the functional annotation of the human genome. We previously performed a subcellular localization screen of 52 proteins encoded on human chromosome 21. In the current study, we compared the experimental localization data to the in silico results generated by nine leading software packages with different prediction resolutions. The comparison revealed striking differences between the programs in the accuracy of their subcellular protein localization predictions. Our results strongly suggest that the recently developed predictors utilizing multiple prediction methods tend to provide significantly better performance over purely sequence-based or homology-based predictions
Discrete Emotion Effects on Lexical Decision Response Times
Our knowledge about affective processes, especially concerning effects on cognitive demands like word processing, is increasing steadily. Several studies consistently document valence and arousal effects, and although there is some debate on possible interactions and different notions of valence, broad agreement on a two dimensional model of affective space has been achieved. Alternative models like the discrete emotion theory have received little interest in word recognition research so far. Using backward elimination and multiple regression analyses, we show that five discrete emotions (i.e., happiness, disgust, fear, anger and sadness) explain as much variance as two published dimensional models assuming continuous or categorical valence, with the variables happiness, disgust and fear significantly contributing to this account. Moreover, these effects even persist in an experiment with discrete emotion conditions when the stimuli are controlled for emotional valence and arousal levels. We interpret this result as evidence for discrete emotion effects in visual word recognition that cannot be explained by the two dimensional affective space account
TESTLoc: protein subcellular localization prediction from EST data
Abstract Background The eukaryotic cell has an intricate architecture with compartments and substructures dedicated to particular biological processes. Knowing the subcellular location of proteins not only indicates how bio-processes are organized in different cellular compartments, but also contributes to unravelling the function of individual proteins. Computational localization prediction is possible based on sequence information alone, and has been successfully applied to proteins from virtually all subcellular compartments and all domains of life. However, we realized that current prediction tools do not perform well on partial protein sequences such as those inferred from Expressed Sequence Tag (EST) data, limiting the exploitation of the large and taxonomically most comprehensive body of sequence information from eukaryotes. Results We developed a new predictor, TESTLoc, suited for subcellular localization prediction of proteins based on their partial sequence conceptually translated from ESTs (EST-peptides). Support Vector Machine (SVM) is used as computational method and EST-peptides are represented by different features such as amino acid composition and physicochemical properties. When TESTLoc was applied to the most challenging test case (plant data), it yielded high accuracy (~85%). Conclusions TESTLoc is a localization prediction tool tailored for EST data. It provides a variety of models for the users to choose from, and is available for download at http://megasun.bch.umontreal.ca/~shenyq/TESTLoc/TESTLoc.html</p
Imbalanced Multi-Modal Multi-Label Learning for Subcellular Localization Prediction of Human Proteins with Both Single and Multiple Sites
It is well known that an important step toward understanding the functions of a protein is to determine its subcellular location. Although numerous prediction algorithms have been developed, most of them typically focused on the proteins with only one location. In recent years, researchers have begun to pay attention to the subcellular localization prediction of the proteins with multiple sites. However, almost all the existing approaches have failed to take into account the correlations among the locations caused by the proteins with multiple sites, which may be the important information for improving the prediction accuracy of the proteins with multiple sites. In this paper, a new algorithm which can effectively exploit the correlations among the locations is proposed by using Gaussian process model. Besides, the algorithm also can realize optimal linear combination of various feature extraction technologies and could be robust to the imbalanced data set. Experimental results on a human protein data set show that the proposed algorithm is valid and can achieve better performance than the existing approaches
The JWST Early Release Science Program for Direct Observations of Exoplanetary Systems II: A 1 to 20 Micron Spectrum of the Planetary-Mass Companion VHS 1256-1257 b
We present the highest fidelity spectrum to date of a planetary-mass object.
VHS 1256 b is a 20 M widely separated (8\arcsec, a =
150 au), young, planetary-mass companion that shares photometric colors and
spectroscopic features with the directly imaged exoplanets HR 8799 c, d, and e.
As an L-to-T transition object, VHS 1256 b exists along the region of the
color-magnitude diagram where substellar atmospheres transition from cloudy to
clear. We observed VHS 1256~b with \textit{JWST}'s NIRSpec IFU and MIRI MRS
modes for coverage from 1 m to 20 m at resolutions of 1,000 -
3,700. Water, methane, carbon monoxide, carbon dioxide, sodium, and potassium
are observed in several portions of the \textit{JWST} spectrum based on
comparisons from template brown dwarf spectra, molecular opacities, and
atmospheric models. The spectral shape of VHS 1256 b is influenced by
disequilibrium chemistry and clouds. We directly detect silicate clouds, the
first such detection reported for a planetary-mass companion.Comment: Accepted ApJL Iterations of spectra reduced by the ERS team are
hosted at this link:
https://github.com/bemiles/JWST_VHS1256b_Reduction/tree/main/reduced_spectr
The JWST Early Release Science Program for Direct Observations of Exoplanetary Systems IV: NIRISS Aperture Masking Interferometry Performance and Lessons Learned
We present a performance analysis for the aperture masking interferometry
(AMI) mode on board the James Webb Space Telescope Near Infrared Imager and
Slitless Spectrograph (JWST/NIRISS). Thanks to self-calibrating observables,
AMI accesses inner working angles down to and even within the classical
diffraction limit. The scientific potential of this mode has recently been
demonstrated by the Early Release Science (ERS) 1386 program with a deep search
for close-in companions in the HIP 65426 exoplanetary system. As part of ERS
1386, we use the same dataset to explore the random, static, and calibration
errors of NIRISS AMI observables. We compare the observed noise properties and
achievable contrast to theoretical predictions. We explore possible sources of
calibration errors, and show that differences in charge migration between the
observations of HIP 65426 and point-spread function calibration stars can
account for the achieved contrast curves. Lastly, we use self-calibration tests
to demonstrate that with adequate calibration, NIRISS AMI can reach contrast
levels of mag. These tests lead us to observation planning
recommendations and strongly motivate future studies aimed at producing
sophisticated calibration strategies taking these systematic effects into
account. This will unlock the unprecedented capabilities of JWST/NIRISS AMI,
with sensitivity to significantly colder, lower mass exoplanets than
ground-based setups at orbital separations inaccessible to JWST coronagraphy.Comment: 20 pages, 12 figures, submitted to AAS Journal
The \textit{JWST} Early Release Science Program for Direct Observations of Exoplanetary Systems III: Aperture Masking Interferometric Observations of the star HIP\,65426 at
We present aperture masking interferometry (AMI) observations of the star HIP
65426 at as a part of the \textit{JWST} Direct Imaging Early
Release Science (ERS) program obtained using the Near Infrared Imager and
Slitless Spectrograph (NIRISS) instrument. This mode provides access to very
small inner working angles (even separations slightly below the Michelson limit
of for an interferometer), which are inaccessible with the
classical inner working angles of the \textit{JWST} coronagraphs. When combined
with \textit{JWST}'s unprecedented infrared sensitivity, this mode has the
potential to probe a new portion of parameter space across a wide array of
astronomical observations. Using this mode, we are able to achieve a contrast
of \,mag relative to the host star at a separation
of {\sim}0.07\arcsec but detect no additional companions interior to the
known companion HIP\,65426\,b. Our observations thus rule out companions more
massive than 10{-}12\,\rm{M\textsubscript{Jup}} at separations
from HIP\,65426, a region out of reach of ground or
space-based coronagraphic imaging. These observations confirm that the AMI mode
on \textit{JWST} is sensitive to planetary mass companions orbiting at the
water frost line, even for more distant stars at 100\,pc. This result
will allow the planning and successful execution of future observations to
probe the inner regions of nearby stellar systems, opening essentially
unexplored parameter space.Comment: 15 pages, 9 figures, submitted to ApJ Letter
Vector-apodizing phase plate coronagraph: design, current performance, and future development [Invited]
Instrumentatio
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