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{bio,medical} informatics

Tuesday, May 15, 2001

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find related articles. powered by google. BioMedNet Cells in cyberspace promise biology real understanding
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""We in physics are used to studying complex systems, but the level of complexity inherent in biological systems ... is way beyond what we have experience dealing with," said Rajagopal, assistant director of research at the Cavendish Laboratory in the University of Cambridge. "Biological systems are much harder to model as they are in highly non-equilibrium states and you not only have to take into account the flow of matter and energy, but also the flow of information!"

He added: "In biology, the whole is greater than the sum of its parts. We have to move on from the "reductionist" towards an "integrationist" approach.

"With viable computer models of biological systems, we can hope to evaluate hypotheses regarding the behaviour of these systems in their normal and diseased states," said Rajagopal."
find related articles. powered by google. Systems Biology Workbench Development Group Mission
"Our Mission is to develop an integrated, easy-to-use environment, the workbench , which will enable biologists to create, manipulate, display and analyze biological models at molecular, cellular and multicellular levels. We are focusing on biochemical networks including mass action kinetics, metabolic pathways, stochastic simulation, gene expression and regulation."

"One of the key aspects of out project is to facilitate collaboration among existing developers and users of system biology software. We aim to do this by providing an open-source software infrastructure which will enable collaborators to freely use and share each other's computational resources."

redux [02.16.01]
find related articles. powered by google. MIT Technology Review Upstream: Biology in Silico
"Computers capable of mimicking life have long been the stuff of sci-fi nightmares—think The Terminator or 2001's HAL 9000. But for researchers struggling to make sense of vast amounts of new biological data, and for drug companies anxious to cut costs and speed development, having accurate computer simulations of living systems is still a dream. To make that dream come true, they are turning to "in silico biology," building computer models of the intricate processes that take place inside cells, organs, and even people. The ultimate goal: an entire organism modeled in silicon, allowing researchers to test new therapies much as engineers "fly" new airplane designs on supercomputers."

redux [11.27.00]
find related articles. powered by google. BusinessWeek A Software Model That Fathoms the Human Heart?
"What do a Boeing 777 and the human body have in common? Both are complex systems, dependent on millions of complex parts, whether they be a jet-propelled engine or a pumping organ such as the heart. The big difference: Engineers can design and build highly accurate computer models of the way a Boeing 777 will behave in flight. The human heart? Its complexity has long stymied efforts by researchers intent on turning drug development into a predictive science, much like building airplanes.

But that's changing. A handful of companies are developing software that can model single cells, whole organs, cellular metabolism and toxicology, diseases throughout a patient's body, and even an entire clinical trial."

redux [02.24.00]
find related articles. powered by google. HMS Beagle Virtual Cures
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"For a brief period, supplying the data was enough. More genes meant more potential drug targets. But now the victims of the data flood are crying for help. Companies like Entelos, Inc. (Menlo Park, California) are coming to the rescue by building models that integrate all those data into a single, homeostatic, interconnected whole. The models allow researchers to run virtual drug trials to determine the best drug targets, treatment regimens, and patient populations."

Modelers feel that their time has come. "Leaders in the genomics field are all coming to this realization that model building is becoming the rate-limiting step," says Palsson. "There's a major shift taking place in the biological sciences." Math is back, he says, and "biology is going to become quantitative."
find related articles. powered by google. Biospace Virtual Drug Development: Start-ups Put Biology in Motion
"One way of animating our growing store of static information is through computer simulation. It is an area that is beginning to emerge slowly in the life sciences, with only a handful of academic and commercial players active in the area. But for a fledging discipline, there is a great variety in the scope of work being undertaken. While academic labs try to create accurate simulations of red blood cells and simple bacteria, the private companies are taking on bolder projects--simulating human organs and even human diseases in their entirety."
redux [09.06.00]
find related articles. powered by google. UNISCI Nobelist To Lead Web-Based Project On Cell Signaling
"Nobel laureate Dr. Alfred Gilman, chairman of pharmacology at UT Southwestern Medical Center at Dallas, will lead a $10 million-per-year project allowing researchers around the world to pool their efforts in studying one of the biggest unsolved problems in biomedicine -- how cells interact with, or signal, each other."

"Work of these Alliance for Cellular Signaling (AFCS) researchers in the post-genome era ultimately could lead to the development of a "virtual cell" that could be used to test new drugs.”

"When we have a complete virtual cell, it can be used as a drug discovery engine to test drugs on the computer, rather than on cells or animals. It would be a wonderful way to understand what the optimal point would be to place a drug to achieve a specific goal in a specific patient in a specific kind of disease," Gilman said."

"NIGMS has called the AFCS funding "glue grants -- grants to glue together different sorts of people for a common goal," Gilman said. "We actually are gluing together people's brains and their ideas, but the research is not going to be done in their individual labs."

Instead, the researchers will use the Internet as their joint laboratory."
find related articles. powered by google. The Alliance for Cellular Signalling General Goals and Statement of Purpose
"The current and pending availability of complete genomic sequences inspires confidence that complex biological phenomena and systems can be understood completely. These feelings are heightened by rapidly expanding capabilities to manipulate gene content and expression in mammalian cells and organisms, detect protein-protein interactions, and quantify the activities of macromolecules in vivo. Such understanding implies the capacity to predict quantitatively the altered behavior of these systems that results from their genetic or environmental (including pharmacological) perturbation. We can envision, rather than simply imagine, the construction of a virtual cell."

The overall goal of the Alliance for Cellular Signaling is to understand as completely as possible the relationships between sets of inputs and outputs in signaling cells that vary both temporally and spatially. The same goal, stated from a slightly different perspective, is to understand fully how cells interpret signals in a context-dependent manner. This will involve identification of all the proteins that comprise the various signaling systems, the assessment of time-dependent information flow through the systems in both normal and pathological states, and finally the reduction of the mass of detailed data into a set of interacting theoretical models that describe cellular signaling."
redux [08.12.00]
find related articles. powered by google. GenomeBiology Whither genomics?
"The flood of data from genome-wide analysis is transforming biology. We need to develop new, interdisciplinary approaches to convert these data into information about the components and structures of individual biological pathways and to use the resulting information to yield knowledge about general principles that explain the functions and evolution of life."

"Genomics increases the chance that biology will experience a split like the one in physics, between those who collect and those who analyze data. This will challenge the majority of biologists who believe that modeling, simulation, and theory have little to contribute to biology. This prejudice rests on insecurity engendered by most biologists' weakness in mathematics (including my own) and previous efforts to model systems using more variables than there were data points. If we keep clinging to this prejudice, we will drown in a sea of data."

redux [07.13.00]
find related articles. powered by google. Nature Segmentation in silico
"A new mathematical biology is emerging. Building on experimental data from developing organisms, it uses the power of computational methods to explore the properties of real gene networks."

"Our understanding of gene networks is at an early stage. We perceive their complexity only after it has been filtered by the limitations of the techniques used to study them. Genome databases and DNA-chip technology, which enables huge numbers of genes to be screened for activity, will undoubtedly provide more, and much more complicated, data than anything produced by Drosophila genetics. If a relatively simple gene network such as the segment-polarity system is hard to understand intuitively, we can be certain that modelling will be essential to make sense of the flood of new data.

But this will not be elegant theoretical modelling: rather, it will be rooted in the arbitrary complexity of evolved organisms. The task will require a breed of biologist–mathematician as familiar with handling differential equations as with the limitations of messy experimental data. There will be plenty of vacancies, and, on present showing, not many qualified applicants."

redux [04.05.00]
find related articles. powered by google. HMS Beagle Are Computers Evolving in Biology?
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"I suspect that although the new enthusiasm for computers in biology is genuine, it overlooks some basic problems in implementation. The basic difficulty, as I see it, is that although biologists use computers, they do not trust everything that comes out of them. It is one thing to use them to print up nice-looking graphs, but it is an entirely different matter to use them to think better."

"Francis Crick was once quoted as saying that no biologist had ever made a discovery using a mathematical model. I would reply that no biologist has ever made a discovery by running an electrophoretic gel. They make discoveries by using their brains. Computers, like all scientific tools, are only as good as the person who uses them. If biologists don't understand how computer models are constructed, they won't know their strengths and limitations. Without some foundation of trust, biologists will be unlikely to utilize or accept this powerful method of data analysis."

redux [02.24.00]
find related articles. powered by google. Science Revealing Uncertainties in Computer Models
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"Computer simulations give the impression of precision, but they are founded on a raft of assumptions, simplifications, and outright errors. New tools are needed, scientists say, to quantify the uncertainties inherent in calculations and to evaluate the validity of the models. But making uncertainties evident is a tough challenge, as evidenced by several recent workshops.”

[ rhetoric ]

Bioinformatics will be at the core of biology in the 21st century. In fields ranging from structural biology to genomics to biomedical imaging, ready access to data and analytical tools are fundamentally changing the way investigators in the life sciences conduct research and approach problems. Complex, computationally intensive biological problems are now being addressed and promise to significantly advance our understanding of biology and medicine. No biological discipline will be unaffected by these technological breakthroughs.


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