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Search Results: 1 - 10 of 6183 matches for " Changhui Ge "
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Effects of varying Notch1 signal strength on embryogenesis and vasculogenesis in compound mutant heterozygotes
Changhui Ge, Pamela Stanley
BMC Developmental Biology , 2010, DOI: 10.1186/1471-213x-10-36
Abstract: Mouse embryos expressing the hypomorphic Notch112f allele, in combination with the inactive Notch1lbd allele which lacks the Notch1 ligand binding domain, died at ~E11.5-12.5. Notch112f/lbd ES cells signaled less well than Notch112f/12f ES cells but more strongly than Notch1lbd/lbd ES cells. However, vascular defects in Notch112f/lbd yolk sac were severe and similar to Notch1lbd/lbd yolk sac. By contrast, vascular disorganization was milder in Notch112f/lbd compared to Notch1lbd/lbd embryos. The expression of Notch1 target genes was low in Notch112f/lbd yolk sac and embryo head, whereas Vegf and Vegfr2 transcripts were increased. The severity of the compound heterozygous Notch112f/lbd yolk sac phenotype suggested that the allelic products may functionally interact. By contrast, compound heterozygotes with Notch112f in combination with a Notch1 null allele (Notch1tm1Con) were capable of surviving to birth.Notch1 signaling in Notch112f/lbd compound heterozygous embryos is more defective than in compound heterozygotes expressing a hypomorphic Notch112f allele and a Notch1 null allele. The data suggest that the gene products Notch1lbd and Notch112f interact to reduce the activity of Notch112f.Notch transmembrane receptors are important regulators of cell fate determination in numerous cell types [1-3]. Notch receptors in Drosophila and mammals are covalently modified with O-fucose on many epidermal growth factor-like (EGF) repeats of the extracellular domain [4]. An important O-fucose site resides in epidermal growth factor-like repeat 12 (EGF12) which, together with EGF11, is required for canonical Notch ligand binding to Drosophila Notch [5-7] and to mammalian Notch1 [8]. A point mutation that precludes the addition of fucose to EGF12 in Drosophila Notch results in enhanced binding of both Delta and Serrate Notch ligands, and a hyperactive Notch that is refractory to Fringe [9]. However, the same mutation (Notch112f) in cultured mammalian cells gives markedly reduced
In vivo consequences of deleting EGF repeats 8–12 including the ligand binding domain of mouse Notch1
Changhui Ge, Tongyi Liu, Xinghua Hou, Pamela Stanley
BMC Developmental Biology , 2008, DOI: 10.1186/1471-213x-8-48
Abstract: Notch1lbd/lbd embryos died at mid-gestation with a phenotype indistinguishable from Notch1 null mutants. In embryonic stem (ES) cells, Notch1lbd was expressed on the cell surface at levels equivalent to wild type Notch1, but Delta1 binding was reduced to the same level as in Notch1 null cells. In an ES cell co-culture assay, Notch signaling induced by Jagged1 or Delta1 was reduced to a similar level in Notch1lbdand Notch1 null cells. However, the Notch1lbd/lbd allele was expressed similarly to wild type Notch1 in Notch1lbd/lbd ES cells and embryos at E8.75, indicating that Notch1 signaling is not essential for the Notch1 gene to be expressed. In addition, maternal and zygotic Notch1 mutant blastocysts developed through gastrulation.Mouse Notch1 lacking the ligand binding domain is expressed at the cell surface but does not signal in response to the canonical Notch ligands Delta1 and Jagged1. Homozygous Notch1lbd/lbd mutant embryos die at ~E10 similar to Notch1 null embryos. While Notch1 is expressed in oocytes and blastocysts, Notch1 signaling via canonical ligands is dispensable during oogenesis, blastogenesis, implantation and gastrulation.Notch1 is a heterodimeric, type I transmembrane receptor that is required for cell fate decisions throughout the metazoa [1,2]. The Notch1 extracellular domain contains 36 tandem epidermal growth factor-like (EGF) repeats, and three Lin/Notch repeats. Of the 36 EGF repeats in Drosophila Notch, deletion of only EGF repeats 11 and 12 prohibits the binding of the Notch ligands Delta and Serrate in in vitro binding assays [3,4]. Notch signaling in mammals is also initiated by binding to canonical Notch ligands (Delta and Jagged) on adjacent cells. Ligand binding activates Notch signaling through two proteolytic cleavage events, first in the extracellular domain by the ADAM10 metalloprotease [5], and subsequently in the transmembrane domain by a presenilin complex with γ-secretase activity [6,7]. The released Notch intracellular doma
Detecting Periodicity Associated with the Alpha-Helix Structure Using Fourier Transform  [PDF]
Wen Cheng, Changhui Yan
Computational Molecular Bioscience (CMB) , 2012, DOI: 10.4236/cmb.2012.24011
Abstract: Alpha helix is a common type of secondary structure in the protein structure that consists of repeating helical turns. Patterns in the protein sequences that cause this repetitive pattern in the structure have long been sought. We used the discrete Fourier transform (DFT) to detect the periodicity signals correlated to the helical structure. We studied the distribution of multiple properties along the protein sequence, and found a property that showed strong periodicity correlated with the helical structure. Using a short-time Fourier transform (STFT) method, we investigated the amplitude of the periodical signals at each amino acid position. The results show that residues in the helix structure tend to display higher amplitudes than residues outside of the helices. This tendency is dramatically strengthen when sequence profiles obtained from multiple alignment were used to detect the periodicity. A simple method that predicted helices based on the amplitude yielded overall true positive rate (TPR) of 63%, 49% sensitivity, 72% specificity, and 0.22 Matthews Correlation Coefficient (MCC). The performance seemed to depend on the length of helices that the proteins had.
A discontinuous Galerkin method on kinetic flocking models
Changhui Tan
Mathematics , 2014,
Abstract: We study kinetic representations of flocking models. They arise from agent-based models for self-organized dynamics, such as Cucker-Smale and Motsch-Tadmor models. We prove flocking behavior for the kinetic descriptions of flocking systems, which indicates a concentration in velocity variable in infinite time. We propose a discontinuous Galerkin method to treat the asymptotic $\delta$-singularity, and construct high order positive preserving scheme to solve kinetic flocking systems.
Identification of deleterious non-synonymous single nucleotide polymorphisms using sequence-derived information
Jing Hu, Changhui Yan
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-297
Abstract: We compiled a set of 686 features that were derived from protein sequence. For each feature, the distance between the wild-type residue and mutant-type residue was computed. Then a greedy approach was used to select the features that were useful for the classification of SAPs. 10 features were selected. Using the selected features, a decision tree method can achieve 82.6% overall accuracy with 0.607 Matthews Correlation Coefficient (MCC) in cross-validation. When tested on an independent set that was not seen by the method during the training and feature selection, the decision tree method achieves 82.6% overall accuracy with 0.604 MCC. We also evaluated the proposed method on all SAPs obtained from the Swiss-Prot, the method achieves 0.42 MCC with 73.2% overall accuracy. This method allows users to make reliable predictions when protein structures are not available. Different from previous studies, in which only a small set of features were arbitrarily chosen and considered, here we used an automated method to systematically discover useful features from a large set of features well-annotated in public databases.The proposed method is a useful tool for the classification of SAPs, especially, when the structure of the protein is not available.It is estimated that around 90% of human genetic variations are differences in single bases of DNA, known as single nucleotide polymorphisms (SNPs) [1]. Among them, non-synonymous single nucleotide polymorphisms (nsSNPs), also known as single amino acid polymorphism (SAPs), that cause amino acid changes in proteins have the potential to affect both protein structure and protein function [2]. Some of the mutations in SAP sites are not associated with any changes in phenotype and are considered functional neutral, but others bringing deleterious effects to protein function and are responsible for many human genetic diseases [3,4]. Recent years have seen an explosion in the number of SAPs in public databases, such as dbSNP [5], HG
A tool for calculating binding-site residues on proteins from PDB structures
Jing Hu, Changhui Yan
BMC Structural Biology , 2009, DOI: 10.1186/1472-6807-9-52
Abstract: In this study, we have developed a tool for calculating binding-site residues on proteins, TCBRP http://yanbioinformatics.cs.usu.edu:8080/ppbindingsubmit webcite. For an input protein, TCBRP can quickly find all binding-site residues on the protein by automatically combining the information obtained from all PDB structures that consist of the protein of interest. Additionally, TCBRP presents the binding-site residues in different categories according to the interaction type. TCBRP also allows researchers to set the definition of binding-site residues.The developed tool is very useful for the research on protein binding site analysis and prediction.Proteins perform various functions through interactions with other molecules, such as DNA, RNA, proteins, carbohydrates, and ligands. To understand the mechanisms of these interactions, many studies have been performed to analyze the properties of binding sites on proteins, such as residue composition, secondary structure, geometric shape, electrostatic potentials, etc [1-10]. To perform such an analysis, researchers must first identify the amino acid residues (referred to as binding-site residues) that are involved in the interactions. In other studies where the goal is to build computational predictors for predicting functional sites on proteins (e.g. DNA-binding sites, RNA-binding sites, protein-protein binding sites), researchers also need to identify binding-site residues on the training and test sets to train and evaluate their predictors [11-17].In most, if not all, of the above-mentioned studies, the binding-site residues are calculated from the 3-dimensional (3D) structures deposited in Protein Data Bank (PDB) [18]. Usually, researchers collected a non-redundant set of PDB structures, and then calculated binding-sites based on the PDB structures. However, one serious problem with this approach is that a protein may have multiple binding sites that interact with different interacting partners, but one PDB structure
HMM_RA: An Improved Method for Alpha-Helical Transmembrane Protein Topology Prediction
Jing Hu,Changhui Yan
Bioinformatics and Biology Insights , 2008,
Abstract:
HMM_RA: An Improved Method for Alpha-Helical Transmembrane Protein Topology Prediction
Jing Hu,Changhui Yan
Bioinformatics and Biology Insights , 2008,
Abstract: α-helical transmembrane (TM) proteins play important and diverse functional roles in cells. The ability to predict the topology of these proteins is important for identifying functional sites and inferring function of membrane proteins. This paper presents a Hidden Markov Model (referred to as HMM_RA) that can predict the topology of α-helical transmembrane proteins with improved performance. HMM_RA adopts the same structure as the HMMTOP method, which has five modules: inside loop, inside helix tail, membrane helix, outside helix tail and outside loop. Each module consists of one or multiple states. HMM_RA allows using reduced alphabets to encode protein sequences. Thus, each state of HMM_RA is associated with n emission probabilities, where n is the size of the reduced alphabet set. Direct comparisons using two standard data sets show that HMM_RA consistently outperforms HMMTOP and TMHMM in topology prediction. Specifically, on a high-quality data set of 83 proteins, HMM_RA outperforms HMMTOP by up to 7.6% in topology accuracy and 6.4% in α-helices location accuracy. On the same data set, HMM_RA outperforms TMHMM by up to 6.4% in topology accuracy and 2.9% in location accuracy. Comparison also shows that HMM_RA achieves comparable performance as Phobius, a recently published method.
Critical thresholds in flocking hydrodynamics\\with nonlocal alignment
Eitan Tadmor,Changhui Tan
Mathematics , 2014, DOI: 10.1098/rsta.2013.0401
Abstract: We study the large-time behavior of Eulerian systems augmented with non-local alignment. Such systems arise as hydrodynamic descriptions of agent-based models for self-organized dynamics, e.g., Cucker-Smale and Motsch-Tadmor models \cite{CS,MT}. We prove that in analogy with the agent-based models, the presence of non-local alignment enforces \emph{strong} solutions to self-organize into a macroscopic flock. This then raises the question of existence of such strong solutions. We address this question in one- and two-dimensional setups, proving global regularity for \emph{sub-critical} initial data. Indeed, we show that there exist \emph{critical thresholds} in the phase space of initial configuration which dictate the global regularity vs. a finite time blow-up. In particular, we explore the regularity of nonlocal alignment in the presence of vacuum.
An Exact Rescaling Velocity Method for some Kinetic Flocking Models
Thomas Rey,Changhui Tan
Mathematics , 2014,
Abstract: In this work, we discuss kinetic descriptions of flocking models, of the so-called Cucker-Smale and Motsch-Tadmor types. These models are given by Vlasov-type equations where the interactions taken into account are only given long-range bi-particles interaction potential. We introduce a new exact rescaling velocity method, inspired by a recent work of Filbet and Rey, allowing to observe numerically the flocking behavior of the solutions to these equations, without a need of remeshing or taking a very fine grid in the velocity space. To stabilize the exact method, we also introduce a modification of the classical upwind finite volume scheme which preserves the physical properties of the solution, such as momentum conservation.
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