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Fazal, Z.

Publications and source records attributed to Fazal, Z..

2 recordsLinked to original sources

Arterial blood contrast (ABC) enabled by magnetization transfer (MT): a novel MRI technique for enhancing the measurement of brain activation changes

Functional brain imaging in humans is almost exclusively performed using blood oxygenation level dependent (BOLD) contrast. This typically requires a period of tens of milliseconds after excitation of the spin system to achieve maximum contrast, leading to inefficient use of acquisition time, reduced image quality, and inhomogeneous sensitivity throughout the cortex. We utilise magnetisation transfer to suppress the signal differentially from grey matter relative to blood so that the local increase in blood volume associated with brain activation (mainly occurring in the arterioles and capillaries) will increase the measured signal. Arterial blood contrast (ABC) is additive to the residual BOLD effect, but will have its maximum value at the time of excitation. We measured brain activation using combined ABC and residual BOLD contrast at different times post-excitation and compared this to BOLD data acquired under otherwise identical conditions. We conclude that using ABC and measuring shortly after excitation gives comparable sensitivity to standard BOLD but will provide greater efficiency, spatial specificity, improved image quality, and lower inter-subject variability. ABC offers new perspectives for performing functional MRI.

neuroscience↗

Using Optimal F-Measure and Random Resampling in Gene Ontology Enrichment Calculations

BackgroundA central question in bioinformatics is how to minimize arbitrariness and bias in analysis of patterns of enrichment in data. A prime example of such a question is enrichment of gene ontology (GO) classes in lists of genes. Our paper deals with two issues within this larger question. One is how to calculate the false discovery rate (FDR) within a set of apparently enriched ontologies, and the second how to set that FDR within the context of assessing significance for addressing biological questions, to answer these questions we compare a random resampling method with a commonly used method for assessing FDR, the Benjamini-Hochberg (BH) method. We further develop a heuristic method for evaluating Type II (false negative) errors to enable utilization of F-Measure binary classification theory for distinguishing \"significant\" from \"non-significant\" degrees of enrichment.\n\nResultsThe results show the preferability and feasibility of random resampling assessment of FDR over the analytical methods with which we compare it. They also show that the reasonableness of any arbitrary threshold depends strongly on the structure of the dataset being tested, suggesting that the less arbitrary method of F-measure optimization to determine significance threshold is preferable.\n\nConclusionTherefore, we suggest using F-measure optimization instead of placing an arbitrary threshold to evaluate the significance of Gene Ontology Enrichment results, and using resampling to replace analytical methods

bioinformatics↗