Biomedical subjects

Huai Li

Publications and source records attributed to Huai Li.

10 recordsLinked to original sources

PubMed2006

The discovery of transcriptional modules by a two-stage matrix decomposition approach.

MOTIVATION: We address the problem of identifying gene transcriptional modules from gene expression data by proposing a new approach. Genes mostly interact with each other to form transcriptional modules for context-specific cellular activities or functions. Unraveling such transcriptional modules is important for understanding biological network, deciphering regulatory mechanisms and identifying biomarkers. METHOD: The proposed algorithm is based on two-stage matrix decomposition. We first model microarray data as non-linear mixtures and adopt the non-linear independent component analysis to reduce the non-linear distortion and separate the data into independent latent components. We then apply the probabilistic sparse matrix decomposition approach to model the 'hidden' expression profiles of genes across the independent latent components as linear weighted combinations of a small number of transcriptional regulator profiles. Finally, we propose a general scheme for identifying gene modules from the outcomes of the matrix decomposition. RESULTS: The proposed algorithm partitions genes into non-mutually exclusive transcriptional modules, independent from expression profile similarity measurement. The modules contain genes with not only similar but different expression patterns, and show the highest enrichment of biological functions in comparison with those by other methods. The usefulness of the algorithm was validated by a yeast microarray data analysis. AVAILABILITY: The software is available upon request to the authors.

Algorithms↗

PubMed2006

Cross-species transcriptional profiles establish a functional portrait of embryonic stem cells.

An understanding of the regulatory mechanisms responsible for pluripotency in embryonic stem cells (ESCs) is critical for realizing their potential in medicine and science. Significant similarities exist among ESCs harvested from different species, yet major differences have also been observed. Here, by cross-species analysis of a large set of functional categories and all transcription factors and growth factors, we reveal conserved and divergent functional landscapes underlining fundamental and species-specific mechanisms that regulate ESC development. Global transcriptional trends derived from all expressed genes, instead of differentially expressed genes alone, were examined, allowing for a higher discriminating power in the functional portrait. We demonstrate that cross-species correlation of transcriptional changes that occur upon ESC differentiation is a powerful predictor of ESC-important biological pathways and functional cores within a pathway. Hundreds of functional modules, as defined by Gene Ontology, were associated with conserved expression patterns but bear no overt relationship to ESC development, suggestive of new mechanisms critical to ESC pluripotency. Yet other functional modules were not conserved; instead, they were significantly up-regulated in ESCs of either species, suggestive of species-specific regulation. The comparisons of ESCs across species and between human ESCs and embryonal carcinoma stem cells suggest that while pluripotency as an essential function in multicellular organisms is conserved throughout evolution, mechanisms primed for differentiation are less conserved and contribute substantially to the differences among stem cells derived from different tissues or species. Our findings establish a basis for defining the "stemness" properties of ESCs from the perspective of functional conservation and variation. The data and analyses resulting from this study provide a framework for new hypotheses and research directions and a public resource for functional genomics of ESCs.

Animals↗

PubMed2006

Genome wide profiling of human embryonic stem cells (hESCs), their derivatives and embryonal carcinoma cells to develop base profiles of U.S. Federal government approved hESC lines.

BACKGROUND: In order to compare the gene expression profiles of human embryonic stem cell (hESC) lines and their differentiated progeny and to monitor feeder contaminations, we have examined gene expression in seven hESC lines and human fibroblast feeder cells using Illumina bead arrays that contain probes for 24,131 transcript probes. RESULTS: A total of 48 different samples (including duplicates) grown in multiple laboratories under different conditions were analyzed and pairwise comparisons were performed in all groups. Hierarchical clustering showed that blinded duplicates were correctly identified as the closest related samples. hESC lines clustered together irrespective of the laboratory in which they were maintained. hESCs could be readily distinguished from embryoid bodies (EB) differentiated from them and the karyotypically abnormal hESC line BG01V. The embryonal carcinoma (EC) line NTera2 is a useful model for evaluating characteristics of hESCs. Expression of subsets of individual genes was validated by comparing with published databases, MPSS (Massively Parallel Signature Sequencing) libraries, and parallel analysis by microarray and RT-PCR. CONCLUSION: we show that Illumina's bead array platform is a reliable, reproducible and robust method for developing base global profiles of cells and identifying similarities and differences in large number of samples.

Carcinoma, Embryonal↗

PubMed2006

Transcriptome coexpression map of human embryonic stem cells.

BACKGROUND: Human embryonic stem (ES) cells hold great promise for medicine and science. The transcriptome of human ES cells has been studied in detail in recent years. However, no systematic analysis has yet addressed whether gene expression in human ES cells may be regulated in chromosomal domains, and no chromosomal domains of coexpression have been identified. RESULTS: We report the first transcriptome coexpression map of the human ES cell and the earliest stage of ES differentiation, the embryoid body (EB), for the analysis of how transcriptional regulation interacts with genomic structure during ES self-renewal and differentiation. We determined the gene expression profiles from multiple ES and EB samples and identified chromosomal domains showing coexpression of adjacent genes on the genome. The coexpression domains were not random, with significant enrichment in chromosomes 8, 11, 16, 17, 19, and Y in the ES state, and 6, 11, 17, 19 and 20 in the EB state. The domains were significantly associated with Giemsa-negative bands in EB, yet showed little correlation with known cytogenetic structures in ES cells. Different patterns of coexpression were revealed by comparative transcriptome mapping between ES and EB. CONCLUSION: The findings and methods reported in this investigation advance our understanding of how genome organization affects gene expression in human ES cells and help to identify new mechanisms and pathways controlling ES self-renewal or differentiation.

Animals↗

PubMed2006

Mechanisms controlling embryonic stem cell self-renewal and differentiation.

Embryonic stem (ES) cells are pluripotent cells with indefinite replication potential and ability to differentiate into all types of cells. An understanding of the regulatory mechanisms responsible for pluripotency in ES cells is critical for realizing their potential in regenerative medicine and science. Cross-species studies on ES cells have identified pathways and networks that are either fundamental to or species-specific for self-renewal and differentiation. Although pluripotency as an essential function in multicellular organisms is conserved through evolution, mechanisms primed for differentiation contribute substantially to the differences among stem cells derived from different tissues or species. Transcriptome mapping analysis has determined the chromosomal domains of gene coexpression patterns specific to the ES state and demonstrated that regulation of ES cell development is operative at both the local chromosomal domain level and global level. Combinatorial signals from multiple pathways regulate the expression of key intrinsic factors critical for ES cell fate determination. The regulatory core formed by Oct4, Sox2, and Nanog, in particular, activates genes critical for self-renewal and represses genes initiating differentiation, controlling ES cell pluripotency. Here, we review recent findings on mechanisms controlling ES cell development. By integrating data from different sources, we present a global picture of how ES cells reach the decision of self-renewal or differentiation.

Animals↗

PubMed2005

Systematic intervention of transcription for identifying network response to disease and cellular phenotypes.

MOTIVATION: A major challenge in post-genomic research has been to understand how physiological and pathological phenotypes arise from the networks of expressed genes. Here, we addressed this issue by developing an algorithm to mimic the behavior of regulatory networks in silico and to identify the dynamic response to disease and changing cellular conditions. RESULTS: With regulatory pathway and gene expression data as input, the algorithm provides quantitative assessments of a wide range of responses, including susceptibility to disease, potential usefulness of a given drug, or consequences to such external stimuli as pharmacological interventions or caloric restriction. The algorithm is particularly amenable to the analysis of systems that are difficult to recapitulate in vitro, yet they may have important clinical value. The hypotheses derived from the algorithm were biologically relevant and were successfully validated via independent experiments, as illustrated here in the analysis of the leukemia-associated BCR-ABL pathway and the insulin/IGF pathway related to longevity. The algorithm correctly identified the leukemia drug target and genes important for longevity, and also provided new insights into our understanding of these two processes. AVAILABILITY: The software package is available upon request to the authors.

Aging↗

PubMed2003

Optimization of wavelet decomposition for image compression and feature preservation.

A neural-network-based framework has been developed to search for an optimal wavelet kernel that can be used for a specific image processing task. In this paper, a linear convolution neural network was employed to seek a wavelet that minimizes errors and maximizes compression efficiency for an image or a defined image pattern such as microcalcifications in mammograms and bone in computed tomography (CT) head images. We have used this method to evaluate the performance of tap-4 wavelets on mammograms, CTs, magnetic resonance images, and Lena images. We found that the Daubechies wavelet or those wavelets with similar filtering characteristics can produce the highest compression efficiency with the smallest mean-square-error for many image patterns including general image textures as well as microcalcifications in digital mammograms. However, the Haar wavelet produces the best results on sharp edges and low-noise smooth areas. We also found that a special wavelet whose low-pass filter coefficients are 0.32252136, 0.85258927, 1.38458542, and -0.14548269) produces the best preservation outcomes in all tested microcalcification features including the peak signal-to-noise ratio, the contrast and the figure of merit in the wavelet lossy compression scheme. Having analyzed the spectrum of the wavelet filters, we can find the compression outcomes and feature preservation characteristics as a function of wavelets. This newly developed optimization approach can be generalized to other image analysis applications where a wavelet decomposition is employed.

Algorithms↗

PubMed2003

Identification of signature genes by microarray for acute myeloid leukemia without maturation and acute promyelocytic leukemia with t(15;17)(q22;q12)(PML/RARalpha).

Acute myeloid leukemia (AML) has distinct subgroups characterized by different maturation and specific chromosomal translocation. In order to gain insight into the gene expression activities in AML, we carried out a gene expression profiling study with 21 AML samples using cDNA microarrays, focusing on acute promyelocytic leukemia with specific translocation t(15;17)(q22;q12) [French-American-British or FAB-M3 with t(15;17)] and AML without maturation (FAB-M1) characterized by morphologically and phenotypically immature AML blasts and no recurrent chromosomal abnormalities. Using a multivariate sigma-classifier algorithm, we identified 33 strong feature genes that distinguish FAB-M3 with t(15;17) from other AML samples, and 24 strong feature genes that classify FAB-M1. A direct comparison between FAB-M3 with t(15;17) and FAB-M1 led to selection of 13 strong feature genes. Those genes include some known to be related to leukemogenesis and cell differentiation. RIN1, a gene in the ras pathway, was up-regulated in FAB-M3 with t(15;17). Growth factor-binding protein 2 gene was down-regulated in FAB-M1. Huntingtin gene was up-regulated in FAB-M1. Others include syndecan 4, interleukin-2 receptor beta, folate receptor beta, low affinity immunoglobulin gamma, Fc receptor IIC precursor, insulin-like growth factor binding protein 2, and myeloperoxidase, which are involved in cell differentiation. Overexpression of myeloperoxidase in FAB-M3 cells with t(15;17) compared to FAB-M1 cells is consistent with the conventional cytochemical staining pattern. Thus, the study revealed that a morphologically-defined FAB-M1 subtype has a distinct gene expression signature that contributes to its cell differentiation and proliferation as well as FAB-M3 with a recurrent cytogenetic abnormality t(15;17)(q22;q12).

Algorithms↗

PubMed2002

A multiple circular path convolution neural network system for detection of mammographic masses.

A multiple circular path convolution neural network (MCPCNN) architecture specifically designed for the analysis of tumor and tumor-like structures has been constructed. We first divided each suspected tumor area into sectors and computed the defined mass features for each sector independently. These sector features were used on the input layer and were coordinated by convolution kernels of different sizes that propagated signals to the second layer in the neural network system. The convolution kernels were trained, as required, by presenting the training cases to the neural network. In this study, randomly selected mammograms were processed by a dual morphological enhancement technique. Radiodense areas were isolated and were delineated using a region growing algorithm. The boundary of each region of interest was then divided into 36 sectors using 36 equi-angular dividers radiated from the center of the region. A total of 144 Breast Imaging-Reporting and Data System-based features (i.e., four features per sector for 36 sectors) were computed as input values for the evaluation of this newly invented neural network system. The overall performance was 0.78-0.80 for the areas (Az) under the receiver operating characteristic curves using the conventional feed-forward neural network in the detection of mammographic masses. The performance was markedly improved with Az values ranging from 0.84 to 0.89 using the MCPCNN. This paper does not intend to claim the best mass detection system. Instead it reports a potentially better neural network structure for analyzing a set of the mass features defined by an investigator.

Breast Neoplasms↗

PubMed2002

[Extrahepatic arterial blood supply of hepatocellular carcinoma and interventional treatment].

OBJECTIVE: To study the pattern extrahepatic arteriy supply to hepatocellular carcinoma and catheterization technique for interventional therapy. METHODS: Routine celiac and superior mesenteric artery angiography was done before transcatheter arterial chemoembolization (TACE) for 78 collateral arterial pathways of 62 hepatocellular carcinoma patients. Super selective catheterization and transcatheter dual arterial chemoembolization (TDACE) to extrahepatic arterial and hepatic arteries were performed. RESULTS: Extrahepatic blood supply was found in 43.1% of hepatocellular carcinoma patients. There was close correlation between extrahepatic arterial blood supply and location of tumor. Success rate of super selective extrahepatic artery catheterization was 71.8% by the combined use of RH, Cobra and SP catheters. Follow-up studies revealed reduction of tumor and complete dense deposition of lipiodol. CONCLUSION: Ample extrahepatic arterial blood supply is found in hepatocellular carcinoma. Transcatherdual arterial chemoembolization is effective, necessary and feasible for hepatocellular carcinoma with extrahepatic arterial blood supply.

Adult↗