In a recent paper in Physical Review E 77:016104 (2008), Weixiong Zhang, Ph.D., Washington University associate professor of computer science and engineering and of genetics, along with his Ph.D. student, Jianhua Ruan, published an algorithm (a recipe of computer instructions) to automatically identify communities and their subtle structures in various networks.
Versatile math tool
Zhang and Ruan's algorithm is so versatile that it has been applied to identify the community structure of a network of co-expressed genes involved in bacterial sepsis.
"This is a tool not only for biological research, but also for sociological research," Zhang said. It can determine, for instance, how people interact in social networks and how scientists collaborate in scientific research.
In biological systems there are lots of communities with many proteins involved to form complexes. "We can use this tool to identify structures embedded in the data," Zhang said. "We've identified the substructures of three different RNA polymerase complexes from noisy data, for instance, which are crucial for gene transcription."
Zhang began his computer science career as a specialist in artificial intelligence, but in recent years he has focused more on computational biology. His goal is to use computational means to solve some basic biology problems and those related to human diseases. For example, his group studied a basic problem of the transcription mechanism of microRNAs, which are small, noncoding RNAs that regulate the development and stress responses of nearly all eukaryotic species that have been studied. Using machine learning techniques, Zhang and his collaborators showed that almost all intergenic microRNA genes in four model species, human, mouse, rice and mustard plant (Arabidopsis), are transcribed by RNA polymerase II, which transcribes protein-coding genes. The results were published in PLoS Computational Biology, 3(3):e37 (2007).
Multidisciplinary research that combines computational approaches with biological data is a hallmark of research themes in Zhang's group. As another example, in a paper published in Genome Biology, 7(6):R49 (2006), Zhang and his Ph.D. student, Guandong Wang, developed an algorithm called WordSpy that identifies cis-regulatory elements — short DNA sequences that are critical to the regulation of gene expression — from a large amount of genome sequences.
Stealth from the ancient Greeks
WordSpy was inspired by an old information-hiding technique called stegography, which can be traced back to ancient Greece. As such, their method can be used to analyze not only genomic sequences, but also natural languages. In fact, their method has been extended to segment words and phrases in Chinese.
Aside from studying networks, Zhang also has formed a broad network of collaborations with scientists across the WUSTL campus and outside of the university. The problems he studies are diverse, ranging from stress responses and virus infection in plants, such as rice, to human diseases, including Alzheimer's disease, herpes virus infection, sepsis, cardiac hypertrophy, lung cancer and lung transplantation. The computational tools his group has developed are helping him and his collaborators come to grips with how perturbation to gene expression can lead to complex traits and human diseases as well as how microRNAs regulate gene expression.
Zhang recently was awarded a grant from the Alzheimer's Association to develop computational systems biology methods for analyzing gene expression perturbation in diseased brains. He has been collaborating with scientists in the Washington University School of Medicine and Scripps Institute in La Jolla, Calif., to study roughly 30 postmortem brain samples of people who died from Alzheimer's disease.
"I'm interested in modeling gene expression perturbation in diseased brains and am looking for the genetic signature," Zhang said. "Due to the complexity of Alzheimer's disease, we are developing other tools. It's a polygenic disease, with a lot of genes at work. I'm sure we'll find that a network is involved."
Wexiong Zhang | EurekAlert!
Extremely fine measurements of motion in orbiting supermassive black holes
28.06.2017 | Stanford University
Ultra-compact phase modulators based on graphene plasmons
27.06.2017 | ICFO-The Institute of Photonic Sciences
An international team of scientists has proposed a new multi-disciplinary approach in which an array of new technologies will allow us to map biodiversity and the risks that wildlife is facing at the scale of whole landscapes. The findings are published in Nature Ecology and Evolution. This international research is led by the Kunming Institute of Zoology from China, University of East Anglia, University of Leicester and the Leibniz Institute for Zoo and Wildlife Research.
Using a combination of satellite and ground data, the team proposes that it is now possible to map biodiversity with an accuracy that has not been previously...
Heatwaves in the Arctic, longer periods of vegetation in Europe, severe floods in West Africa – starting in 2021, scientists want to explore the emissions of the greenhouse gas methane with the German-French satellite MERLIN. This is made possible by a new robust laser system of the Fraunhofer Institute for Laser Technology ILT in Aachen, which achieves unprecedented measurement accuracy.
Methane is primarily the result of the decomposition of organic matter. The gas has a 25 times greater warming potential than carbon dioxide, but is not as...
Hydrogen is regarded as the energy source of the future: It is produced with solar power and can be used to generate heat and electricity in fuel cells. Empa researchers have now succeeded in decoding the movement of hydrogen ions in crystals – a key step towards more efficient energy conversion in the hydrogen industry of tomorrow.
As charge carriers, electrons and ions play the leading role in electrochemical energy storage devices and converters such as batteries and fuel cells. Proton...
Scientists from the Excellence Cluster Universe at the Ludwig-Maximilians-Universität Munich have establised "Cosmowebportal", a unique data centre for cosmological simulations located at the Leibniz Supercomputing Centre (LRZ) of the Bavarian Academy of Sciences. The complete results of a series of large hydrodynamical cosmological simulations are available, with data volumes typically exceeding several hundred terabytes. Scientists worldwide can interactively explore these complex simulations via a web interface and directly access the results.
With current telescopes, scientists can observe our Universe’s galaxies and galaxy clusters and their distribution along an invisible cosmic web. From the...
Temperature measurements possible even on the smallest scale / Molecular ruby for use in material sciences, biology, and medicine
Chemists at Johannes Gutenberg University Mainz (JGU) in cooperation with researchers of the German Federal Institute for Materials Research and Testing (BAM)...
19.06.2017 | Event News
13.06.2017 | Event News
13.06.2017 | Event News
28.06.2017 | Awards Funding
28.06.2017 | Earth Sciences
28.06.2017 | Physics and Astronomy