Biomedical subjects

Shihua Zhang

Publications and source records attributed to Shihua Zhang.

6 recordsLinked to original sources

PubMed2025

Spatial transcriptomics-aided localization for single-cell transcriptomics with STALocator.

Single-cell RNA-sequencing (scRNA-seq) techniques can measure gene expression at single-cell resolution but lack spatial information. Spatial transcriptomics (ST) techniques simultaneously provide gene expression data and spatial information. However, the data quality of the spatial resolution or gene coverage is still much lower than the quality of the single-cell transcriptomics data. To this end, we develop a ST-Aided Locator for single-cell transcriptomics (STALocator) to localize single cells to corresponding ST data. Applications on simulated data showed that STALocator performed better than other localization methods. When applied to the human brain and squamous cell carcinoma data, STALocator could robustly reconstruct the relative spatial organization of critical cell populations. Moreover, STALocator could enhance gene expression patterns for Slide-seqV2 data and predict genome-wide gene expression data for fluorescence in situ hybridization (FISH) and Xenium data, leading to the identification of more spatially variable genes and more biologically relevant Gene Ontology (GO) terms compared with the raw data. A record of this paper's transparent peer review process is included in the supplemental information.

Single-Cell Analysis↗

PubMed2006

Identification of functional modules in a PPI network by clique percolation clustering.

Large-scale experiments and data integration have provided the opportunity to systematically analyze and comprehensively understand the topology of biological networks and biochemical processes in cells. Modular architecture which encompasses groups of genes/proteins involved in elementary biological functional units is a basic form of the organization of interacting proteins. Here we apply a graph clustering algorithm based on clique percolation clustering to detect overlapping network modules of a protein-protein interaction (PPI) network. Our analysis of the yeast Sacchromyces cerevisiae suggests that most of the detected modules correspond to one or more experimentally functional modules and half of these annotated modules match well with experimentally determined protein complexes. Our method of analysis can of course be applied to protein-protein interaction data for any species and even other biological networks.

Algorithms↗

PubMed2006

Revealing divergent evolution, identifying circular permutations and detecting active-sites by protein structure comparison.

BACKGROUND: Protein structure comparison is one of the most important problems in computational biology and plays a key role in protein structure prediction, fold family classification, motif finding, phylogenetic tree reconstruction and protein docking. RESULTS: We propose a novel method to compare the protein structures in an accurate and efficient manner. Such a method can be used to not only reveal divergent evolution, but also identify circular permutations and further detect active-sites. Specifically, we define the structure alignment as a multi-objective optimization problem, i.e., maximizing the number of aligned atoms and minimizing their root mean square distance. By controlling a single distance-related parameter, theoretically we can obtain a variety of optimal alignments corresponding to different optimal matching patterns, i.e., from a large matching portion to a small matching portion. The number of variables in our algorithm increases with the number of atoms of protein pairs in almost a linear manner. In addition to solid theoretical background, numerical experiments demonstrated significant improvement of our approach over the existing methods in terms of quality and efficiency. In particular, we show that divergent evolution, circular permutations and active-sites (or structural motifs) can be identified by our method. The software SAMO is available upon request from the authors, or from http://zhangroup.aporc.org/bioinfo/samo/ and http://intelligent.eic.osaka-sandai.ac.jp/chenen/samo.htm. CONCLUSION: A novel formulation is proposed to accurately align protein structures in the framework of multi-objective optimization, based on a sequence order-independent strategy. A fast and accurate algorithm based on the bipartite matching algorithm is developed by exploiting the special features. Convergence of computation is shown in experiments and is also theoretically proven.

Algorithms↗

PubMed2006

Quasiperiodic property in Alu repeats.

We investigate the possible quasiperiodic property in the sequences of Alu repeats, one of typical noncoding DNA sequences. We calculated the quasiperiods of the right and left monomers of Alu repeats of different families with quasiperiodic matrix algorithm. It is interesting that the right monomers of all families show significant quasiperiod 8 in their sequences while the left monomers show quasiperiods 8 or 5. Our results indicate that there exist common quasiperiods in most Alu repeats. This may be helpful to further explore possible functions of Alu repeats.

Algorithms↗

PubMed2005

Comparison of protein structures by multi-objective optimization.

We propose a novel method for solving the structure comparison problem for proteins, based on a decomposition technique. We define the structure alignment as a multi-objective optimization problem with both discrete and continuous variables, i.e., maximizing the number of aligned atoms and minimizing their root mean square distance. By controlling a single distance-related parameter, theoretically we can obtain a variety of optimal alignments corresponding to different optimal matching patterns, i.e., from a large matching portion to a small portion. The number of variables in our algorithm increases with the number of atoms of protein pairs in almost a linear manner. The software is available upon request, or from http://zhangroup.aporc.org/bioinfo/samo/.

Algorithms↗

PubMed2004

[A simulating experimental system for interventional treatment of lung cancer].

In order to go deeply into the researches on the theory of hemodynamics for interventional treatment of lung cancer, we have designed a simulating experimental system. Using the experimental system, we can simulate the operation process and test the effect of drug infusion under a variety of physiological parameters. The parameters that admit of adjustment are: cardiac output, blood pressure of aorta, waveform of pressure, pulse period, blood flow in bronchial artery and different types of catheter, injecting velocity, injecting technique, etc. In addition, the entrance position and blood vessel diameter of small embranchment artery can be changed. In this paper are presented the application of our pH-testing method to natural infusion region and the determined representational shape and size.

Antineoplastic Agents↗