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6 result(s) for "Zheng, Weimou"
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Noninvasive Fetal Trisomy (NIFTY) test: an advanced noninvasive prenatal diagnosis methodology for fetal autosomal and sex chromosomal aneuploidies
Background Conventional prenatal screening tests, such as maternal serum tests and ultrasound scan, have limited resolution and accuracy. Methods We developed an advanced noninvasive prenatal diagnosis method based on massively parallel sequencing. The Noninvasive Fetal Trisomy (NIFTY) test, combines an optimized Student’s t-test with a locally weighted polynomial regression and binary hypotheses. We applied the NIFTY test to 903 pregnancies and compared the diagnostic results with those of full karyotyping. Results 16 of 16 trisomy 21, 12 of 12 trisomy 18, two of two trisomy 13, three of four 45, X, one of one XYY and two of two XXY abnormalities were correctly identified. But one false positive case of trisomy 18 and one false negative case of 45, X were observed. The test performed with 100% sensitivity and 99.9% specificity for autosomal aneuploidies and 85.7% sensitivity and 99.9% specificity for sex chromosomal aneuploidies. Compared with three previously reported z-score approaches with/without GC-bias removal and with internal control, the NIFTY test was more accurate and robust for the detection of both autosomal and sex chromosomal aneuploidies in fetuses. Conclusion Our study demonstrates a powerful and reliable methodology for noninvasive prenatal diagnosis.
Incorporating Ab Initio energy into threading approaches for protein structure prediction
Background Native structures of proteins are formed essentially due to the combining effects of local and distant (in the sense of sequence) interactions among residues. These interaction information are, explicitly or implicitly, encoded into the scoring function in protein structure prediction approaches—threading approaches usually measure an alignment in the sense that how well a sequence adopts an existing structure; while the energy functions in Ab Initio methods are designed to measure how likely a conformation is near-native. Encouraging progress has been observed in structure refinement where knowledge-based or physics-based potentials are designed to capture distant interactions. Thus, it is interesting to investigate whether distant interaction information captured by the Ab Initio energy function can be used to improve threading, especially for the weakly/distant homologous templates. Results In this paper, we investigate the possibility to improve alignment-generating through incorporating distant interaction information into the alignment scoring function in a nontrivial approach. Specifically, the distant interaction information is introduced through employing an Ab Initio energy function to evaluate the “partial” decoy built from an alignment. Subsequently, a local search algorithm is utilized to optimize the scoring function. Experimental results demonstrate that with distant interaction items, the quality of generated alignments are improved on 68 out of 127 query-template pairs in Prosup benchmark. In addition, compared with state-to-art threading methods, our method performs better on alignment accuracy comparison. Conclusions Incorporating Ab Initio energy functions into threading can greatly improve alignment accuracy.
A metagenome-wide association study of gut microbiota in type 2 diabetes
Assessment and characterization of gut microbiota has become a major research area in human disease, including type 2 diabetes, the most prevalent endocrine disease worldwide. To carry out analysis on gut microbial content in patients with type 2 diabetes, we developed a protocol for a metagenome-wide association study (MGWAS) and undertook a two-stage MGWAS based on deep shotgun sequencing of the gut microbial DNA from 345 Chinese individuals. We identified and validated approximately 60,000 type-2-diabetes-associated markers and established the concept of a metagenomic linkage group, enabling taxonomic species-level analyses. MGWAS analysis showed that patients with type 2 diabetes were characterized by a moderate degree of gut microbial dysbiosis, a decrease in the abundance of some universal butyrate-producing bacteria and an increase in various opportunistic pathogens, as well as an enrichment of other microbial functions conferring sulphate reduction and oxidative stress resistance. An analysis of 23 additional individuals demonstrated that these gut microbial markers might be useful for classifying type 2 diabetes. The authors have developed a new method, metagenome-wide association study (MGWAS), to compare the combined genetic content of the faecal microbiota of healthy people versus patients with type 2 diabetes; they identify multiple microbial species and metabolic pathways that are associated with either cohort and show that some of these may be used as biomarkers. Diabetes and the gut metagenome The incidence of type 2 diabetes is known to correlate with both genetic and environmental factors, and it has been suggested that alterations in the intestinal microbiota may also be involved. Jun Wang and colleagues have developed a novel approach, termed a metagenome-wide association study (MWAS), to compare the combined genetic content of the faecal microbiota between healthy people and those with diabetes. They identify multiple microbial species and metabolic pathways that are associated with either cohort and show that some of these may be used as biomarkers.
The Genomes of Oryza sativa: A History of Duplications
We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000-40,000. Only 2%-3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family.
A Draft Sequence of the Rice Genome (Oryza sativa L. ssp. indica)
We have produced a draft sequence of the rice genome for the most widely cultivated subspecies in China, Oryza sativa L. ssp. indica, by whole-genome shotgun sequencing. The genome was 466 megabases in size, with an estimated 46,022 to 55,615 genes. Functional coverage in the assembled sequences was 92.0%. About 42.2% of the genome was in exact 20-nucleotide oligomer repeats, and most of the transposons were in the intergenic regions between genes. Although 80.6% of predicted Arabidopsis thaliana genes had a homolog in rice, only 49.4% of predicted rice genes had a homolog in A. thaliana. The large proportion of rice genes with no recognizable homologs is due to a gradient in the GC content of rice coding sequences.
genetic variation map for chicken with 2.8 million single-nucleotide polymorphisms
We describe a genetic variation map for the chicken genome containing 2.8 million single-nucleotide polymorphisms (SNPs). This map is based on a comparison of the sequences of three domestic chicken breeds (a broiler, a layer and a Chinese silkie) with that of their wild ancestor, red jungle fowl. Subsequent experiments indicate that at least 90% of the variant sites are true SNPs, and at least 70% are common SNPs that segregate in many domestic breeds. Mean nucleotide diversity is about five SNPs per kilobase for almost every possible comparison between red jungle fowl and domestic lines, between two different domestic lines, and within domestic linesin contrast to the notion that domestic animals are highly inbred relative to their wild ancestors. In fact, most of the SNPs originated before domestication, and there is little evidence of selective sweeps for adaptive alleles on length scales greater than 100 kilobases.