| 1. |
- Khan, Bakht Yawar A., et al.
(författare)
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A Study on Serum Biochemistry and Hematological Profiling of Blue Rock Pigeon (Columba livia) in Multan (Punjab, Pakistan)
- 2011
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Ingår i: Pakistan Journal of Zoology. - 0030-9923. ; 43:5, s. 1012-1014
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Tidskriftsartikel (refereegranskat)abstract
- Thirty wild blue rock pigeons (Columba livia) were caught from Multan city (Pakistan). Hematological values were established for total red blood cells, total white blood cells, packed cell volume, hemoglobin concentration, mean corpuscular volume, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, and differential leukocyte count. Serum bio chemistry values were determined for glucose (294 +/- 95.1), urea (17.9 +/- 4.9 mg/di), cholesterol (250.3 +/- 57.2 mg/di), creatinine (0.41 +/- 0.2 mg/dl), lactate dehydrogenase (1069 +/- 581), total protein (9.8 +/- 0.7 mg/dl), alanine aminotransferase (75.9 +/- 64.3) and aspratate aminotransferase (297.2 +/- 177) as indicator of bird health and can be used in the future as a reference values in hematology and serum biochemistry of blue rock pigeon.
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| 2. |
- Ali, Raja Hashim, et al.
(författare)
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Quantitative synteny scoring improves homology inference and partitioning of gene families
- 2013
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Ingår i: BMC Bioinformatics. - : BioMed Central. - 1471-2105. ; 14, s. S12-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Clustering sequences into families has long been an important step in characterization of genes and proteins. There are many algorithms developed for this purpose, most of which are based on either direct similarity between gene pairs or some sort of network structure, where weights on edges of constructed graphs are based on similarity. However, conserved synteny is an important signal that can help distinguish homology and it has not been utilized to its fullest potential. Results: Here, we present GenFamClust, a pipeline that combines the network properties of sequence similarity and synteny to assess homology relationship and merge known homologs into groups of gene families. GenFamClust identifies homologs in a more informed and accurate manner as compared to similarity based approaches. We tested our method against the Neighborhood Correlation method on two diverse datasets consisting of fully sequenced genomes of eukaryotes and synthetic data. Conclusions: The results obtained from both datasets confirm that synteny helps determine homology and GenFamClust improves on Neighborhood Correlation method. The accuracy as well as the definition of synteny scores is the most valuable contribution of GenFamClust.
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| 3. |
- Peden, John F., et al.
(författare)
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A genome-wide association study in Europeans and South Asians identifies five new loci for coronary artery disease
- 2011
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 43:4, s. 339-344
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies have identified 11 common variants convincingly associated with coronary artery disease (CAD)(1-7), a modest number considering the apparent heritability of CAD(8). All of these variants have been discovered in European populations. We report a meta-analysis of four large genome-wide association studies of CAD, with similar to 575,000 genotyped SNPs in a discovery dataset comprising 15,420 individuals with CAD (cases) (8,424 Europeans and 6,996 South Asians) and 15,062 controls. There was little evidence for ancestry-specific associations, supporting the use of combined analyses. Replication in an independent sample of 21,408 cases and 19,185 controls identified five loci newly associated with CAD (P < 5 x 10(-8) in the combined discovery and replication analysis): LIPA on 10q23, PDGFD on 11q22, ADAMTS7-MORF4L1 on 15q25, a gene rich locus on 7q22 and KIAA1462 on 10p11. The CAD-associated SNP in the PDGFD locus showed tissue-specific cis expression quantitative trait locus effects. These findings implicate new pathways for CAD susceptibility.
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| 4. |
- Tabassam, Ahmad Ali, et al.
(författare)
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Spectrum estimation and spectrum hole opportunities prediction for cognitive radios using higher-order statistics
- 2011
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Ingår i: 2011 Wireless Advanced (WiAd 2011). - Piscataway, NJ : IEEE. - 9781457701092 - 9781457701108 - 9781457701085 ; , s. 213-217
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Konferensbidrag (refereegranskat)abstract
- Cognitive Radio (CR) is a wireless advanced technology which can utilize an unlicensed as well as a licensed spectrum without a harmful interference to the primary users. An unbiased consistent spectrum estimator is required for the primary user’s detection (sensing) for distinguishing the narrow band signals in a noisy environment. Cognitive radio’s hardware solutions available in a commercial market are frequency band constrained at RF Front-End. In multi-dimensional radio spectrum space any of the dimension: time, frequency, code or space can be used as a transmission opportunity. The spectrum hole time opportunistic prediction is a promising solution to determine the free time slots for transmission within a frequency band. This paper presents classical and parametric statistical spectrum estimators for primary user’s detection. It also presents statistical auto-regressive and moving average predictive modeling for grey-hole spectrum opportunities prediction in a time domain for cognitive radios where frequency, code and space (geographical location) are operational constraints. A prototype system for a cognitive radio is built on top of the software-defined radio in a MATLAB/-Simulink and interfaced with an USRP2 main-board and RFX2400 daughter-board from Ettus Research LLC. © 2011 IEEE.
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