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!
Manifestation of quantum distance in flat band materials
05.08.2020 | Institute for Basic Science
First radio detection of an extrasolar planetary system around a main-sequence star
04.08.2020 | Max-Planck-Institut für Radioastronomie
An international research team has found a new approach that may be able to reduce bone loss in osteoporosis and maintain bone health.
Osteoporosis is the most common age-related bone disease which affects hundreds of millions of individuals worldwide. It is estimated that one in three women...
Traditional single-cell sequencing methods help to reveal insights about cellular differences and functions - but they do this with static snapshots only...
“Core-shell” clusters pave the way for new efficient nanomaterials that make catalysts, magnetic and laser sensors or measuring devices for detecting electromagnetic radiation more efficient.
Whether in innovative high-tech materials, more powerful computer chips, pharmaceuticals or in the field of renewable energies, nanoparticles – smallest...
An international research team with Prof. Cornelia Denz from the Institute of Applied Physics at the University of Münster develop for the first time light fields using caustics that do not change during propagation. With the new method, the physicists cleverly exploit light structures that can be seen in rainbows or when light is transmitted through drinking glasses.
Modern applications as high resolution microsopy or micro- or nanoscale material processing require customized laser beams that do not change during...
Although no life has been detected on the Martian surface, a new study from astrophysicist and research scientist at the Center for Space Science at NYU Abu...
23.07.2020 | Event News
21.07.2020 | Event News
07.07.2020 | Event News
05.08.2020 | Physics and Astronomy
05.08.2020 | Health and Medicine
05.08.2020 | Earth Sciences