Information Theory, Evolution and the Origin of Life presents a timely introduction to the use of information theory and coding theory in molecular biology. The genetical information system, because it is linear and digital, resembles the algorithmic language of computers. George Gamow pointed out that the application of Shannon's information theory breaks genetics and molecular biology out of the descriptive mode into the quantitative mode and Dr Yockey develops this theme, discussing how information theory and coding theory can be applied to molecular biology. He discusses how these tools for measuring the information in the sequences of the genome and the proteome are essential for our complete understanding of the nature and origin of life. The author writes for the computer competent reader who is interested in evolution and the origins of life.
The transmission of genomic information from coding sequence to protein structure during protein synthesis is subject to stochastic errors. To analyze transmission limits in the presence of spurious errors, Shannon's noisy channel theorem is applied to a communication channel between amino acid sequences and their structures established from a large-scale statistical analysis of protein atomic coordinates. While Shannon's theorem confirms that in close to native conformations information is transmitted with limited error probability, additional random errors in sequence (amino acid substitutions) and in structure (structural defects) trigger a decrease in communication capacity toward a Shannon limit at 0.010 bits per amino acid symbol at which communication breaks down. In several controls, simulated error rates above a critical threshold and models of unfolded structures always produce capacities below this limiting value. Thus an essential biological system can be realistically modeled as a digital communication channel that is (a) sensitive to random errors and (b) restricted by a Shannon error limit. This forms a novel basis for predictions consistent with observed rates of defective ribosomal products during protein synthesis, and with the estimated excess of mutual information in protein contact potentials.
In the simplest view of transcriptional regulation, the expression of a gene is turned on or off by changes in the concentration of a transcription factor (TF). We use recent data on noise levels in gene expression to show that it should be possible to transmit much more than just one regulatory bit. Realizing this optimal information capacity would require that the dynamic range of TF concentrations used by the cell, the input/output relation of the regulatory module, and the noise in gene expression satisfy certain matching relations, which we derive. These results provide parameter-free, quantitative predictions connecting independently measurable quantities. Although we have considered only the simplified problem of a single gene responding to a single TF, we find that these predictions are in surprisingly good agreement with recent experiments on the Bicoid/Hunchback system in the early Drosophila embryo and that this system achieves ∼90% of its theoretical maximum information transmission.
To understand the structure of a large-scale biological, social, or technological network, it can be helpful to decompose the network into smaller subunits or modules. In this article, we develop an information-theoretic foundation for the concept of modularity in networks. We identify the modules of which the network is composed by finding an optimal compression of its topology, capitalizing on regularities in its structure. We explain the advantages of this approach and illustrate them by partitioning a number of real-world and model networks.
Information theory in biology by Henry Quastler, Editor. 1953. 273 pp. Urbana: University of Illinois Press
There are two kinds of scientific books worth reading. One is the monograph or treatise type, in which a more or less large field of science is presented in a systematic way, and in the form of a product as finished as possible at the given time. This kind of book may be considered a source of knowledge then available. The other type of book may present a collection of chapters or individual articles which do not claim to be a complete and systematic treatment of the subject; however the reader not only finds interesting ideas there, but the reading as such suggests new ideas. Such books are useful. For, although a rough and unfinished idea per se does not even remotely have the value of a well-elaborated scientific study, yet no elaborate study, no important theory, can be developed without first having a few rough ideas.
The book under consideration definitely belongs to the second category: it is a collection of essays. As the editor states in the Introduction (p. 2) : "The papers in this volume are of a very different degree of maturity. They range from authoritative reviews of well-known facts to hesitant and tentative formulations of embryonic ideas." He further states (p. 3): "We are aware of the fact that this volume is largely exploratory."
If the above is to be considered as a shortcoming, then the reviewer does not need to dwell on it, because the editor, and undoubtedly the authors, are fully aware of it, and duly warn the reader. If we evaluate the book from the point of view of how many ideas it suggests to the reader, then, at least so far as this reviewer is concerned, it must be considered a great success.
Background: Elucidating gene regulatory networks is crucial for understanding normal cell physiology and complex pathologic phenotypes. Existing computational methods for the genome-wide ``reverse engineering'' of such networks have been successful only for lower eukaryotes with simple genomes. Here we present ARACNE, a novel algorithm, using microarray expression profiles, specifically designed to scale up to the complexity of regulatory networks in mammalian cells, yet general enough to address a wider range of network deconvolution problems. This method uses an information theoretic approach to eliminate the majority of indirect interactions inferred by co-expression methods. Results: We prove that ARACNE reconstructs the network exactly (asymptotically) if the effect of loops in the network topology is negligible, and we show that the algorithm works well in practice, even in the presence of numerous loops and complex topologies. We assess ARACNE's ability to reconstruct transcriptional regulatory networks using both a realistic synthetic dataset and a microarray dataset from human B cells. On synthetic datasets ARACNE achieves very low error rates and outperforms established methods, such as Relevance Networks and Bayesian Networks. Application to the deconvolution of genetic networks in human B cells demonstrates ARACNE's ability to infer validated transcriptional targets of the c MYC proto-oncogene. We also study the effects of mis estimation of mutual information on network reconstruction, and show that algorithms based on mutual information ranking are more resilient to estimation errors.
MOTIVATION: Traditional sequence distances require an alignment and therefore are not directly applicable to the problem of whole genome phylogeny where events such as rearrangements make full length alignments impossible. We present a sequence distance that works on unaligned sequences using the information theoretical concept of Kolmogorov complexity and a program to estimate this distance.
RESULTS: We establish the mathematical foundations of our distance and illustrate its use by constructing a phylogeny of the Eutherian orders using complete unaligned mitochondrial genomes. This phylogeny is consistent with the commonly accepted one for the Eutherians. A second, larger mammalian dataset is also analyzed, yielding a phylogeny generally consistent with the commonly accepted one for the mammals.
AVAILABILITY: The program to estimate our sequence distance, is available at http://www.cs.cityu.edu.hk/~cssamk/gencomp/GenCompress1.htm. The distance matrices used to generate our phylogenies are available at http://www.math.uwaterloo.ca/~mli/distance.html.
MOTIVATION: As an increasing number of protein structures become available, the need for algorithms that can quantify the similarity between protein structures increases as well. Thus, the comparison of proteins' structures, and their clustering accordingly to a given similarity measure, is at the core of today's biomedical research. In this paper, we show how an algorithmic information theory inspired Universal Similarity Metric (USM) can be used to calculate similarities between protein pairs. The method, besides being theoretically supported, is surprisingly simple to implement and computationally efficient.
RESULTS: Structural similarity between proteins in four different datasets was measured using the USM. The sample employed represented alpha, beta, alpha-beta, tim-barrel, globins and serpine protein types. The use of the proposed metric allows for a correct measurement of similarity and classification of the proteins in the four datasets.
AVAILABILITY: All the scripts and programs used for the preparation of this paper are available at http://www.cs.nott.ac.uk/~nxk/USM/protocol.html. In that web-page the reader will find a brief description on how to use the various scripts and programs.
PMID: 14751983 DOI: 10.1093/bioinformatics/bth031
Living systems are distinguished in nature by their ability to maintain stable, ordered states far from equilibrium. This is despite constant buffeting by thermodynamic forces that, if unopposed, will inevitably increase disorder. Cells maintain a steep transmembrane entropy gradient by continuous application of information that permits cellular components to carry out highly specific tasks that import energy and export entropy. Thus, the study of information storage, flow and utilization is critical for understanding first principles that govern the dynamics of life. Initial biological applications of information theory (IT) used Shannon's methods to measure the information content in strings of monomers such as genes, RNA, and proteins. Recent work has used bioinformatic and dynamical systems to provide remarkable insights into the topology and dynamics of intracellular information networks. Novel applications of Fisher-, Shannon-, and Kullback-Leibler informations are promoting increased understanding of the mechanisms by which genetic information is converted to work and order. Insights into evolution may be gained by analysis of the the fitness contributions from specific segments of genetic information as well as the optimization process in which the fitness are constrained by the substrate cost for its storage and utilization. Recent IT applications have recognized the possible role of nontraditional information storage structures including lipids and ion gradients as well as information transmission by molecular flux across cell membranes. Many fascinating challenges remain, including defining the intercellular information dynamics of multicellular organisms and the role of disordered information storage and flow in disease.
PMID: 17083004 DOI: 10.1007/s11538-006-9141-5
In the last two years, at least 10 law schools have made their grading systems more lenient to give their students a better chance in a soft job market.
Is GPA tampering and grade inflation going too far with changes like this?
Imagine having your back cut open, part of your spine removed, a stabilizing device that resembles a mini oil rig mounted on your back, the outer membrane of your spinal cord sliced open and experimental stem cells injected into it -- all for the advancement of science because it's not expected to benefit you.
Atlanta, Georgia — Imagine having your back cut open, part of your spine removed, a stabilizing device that resembles a mini oil rig mounted on your back, the outer membrane of your spinal cord sliced open and experimental stem cells injected into it — all for the advancement of science because it’s not expected to benefit you.
John Cornick, 51, did just that earlier this month as part of a groundbreaking clinical trial.
Almost a year ago, Cornick was told he had ALS — better known as Lou Gehrig’s disease. The diagnosis left him “fairly devastated,” he says.
He knew the prospects were grim because there is no cure.
But John wasn’t giving up so quickly, nor was his wife, Gina.
“I knew he was a fighter from the beginning and he really wanted to do something,” Gina Cornick says. She found information about a clinical trial on online and immediately signed him up, even though she had no idea where it was being held.
ALS destroys the nerve cells in the brain and spine which control muscle movement. When the brain can no longer tell muscles to move, they eventually die, depriving the patient of the ability to move arms and legs and eventually breathe.
The goal of this phase 1 trial is to determine whether fetal stem cells can safely be injected into the spinal cord. Ultimately, researchers hope to show that these cells may slow or halt the progression of the fatal disease.
But for now, the only goal is establishing safety.
The Cornicks live in North Carolina, just a few hours from Atlanta, Georgia’s Emory University, the site of the trial. It is the first FDA-approved clinical trial to inject fetal stem cells directly into the spinal cord of an adult.
Dr. Jonathan Glass, director of Emory’s ALS center, is overseeing the trial. Cornick and two previous patients in the trial are heroes, says Glass, because at this point, the trial will likely produce only information, not results.
“In reality what do these patients have? Time, families and their life and we’re putting all of these at risk,” says Glass.
Dr. Lucie Bruijn, science director of the ALS Association, says the progress being made in this clinical trial is exciting. “We’ve been able to move it forward … from animal testing now into actual patients.” The treatment had not been tried in humans before.
Glass hopes this trial will lead to a new form of treatment for people with ALS. “We’re testing multiple things: We’re testing the safety of the surgery; we’re testing the cells; we’re testing immunosuppressants[because scientists do not know whether the body will reject the cells].” They are also testing how well Cornick handles this major surgical procedure, says Glass.
“After we’re finished with the first 12 or 18 patients we will know whether this is surgery that patients can tolerate.”
As he was prepped for surgery, Cornick was hopeful but realistic. “Well, of course you’d like to get up and walk … but I know that’s not going to happen.”
The stem cells used in the surgery are shipped overnight from Maryland, where Neuralstem, the company funding the trial, is based. The stem cells’ source is donated tissue from the spinal cord of an 8-week old aborted fetus, which was donated to the company. The company has developed a method that enables growth of millions of stem cells from this single source of human nerve stem cells.
Before the surgery can begin, a technician at Emory has to verify that a majority of stem cells made it to Atlanta alive. At least 70 percent have to be viable. In this case three samples under the microscope showed 85 percent of the cells arrived alive.
Lead researcher Dr. Eva Feldman, a neurologist at the University of Michigan, designed the trial just four years ago. After a lot of animal testing, her team determined that using fetal nerve stems rather than human embryonic or adult stem cells (such as bone marrow stem cells) was most effective, she says.
Stem cells have the ability to turn into different cells in the body. However, human embryonic stem cells, which come from 4- or 5-day-old embryos, also been found to sometimes turn into cancer cells. Fetal stem cells, such as those used in this trial, are a few weeks older and have already taken on a specific identity — in this case nerve cells.
Feldman says the fetal stem cells used in this trial did not become any of the unwanted cell types. “That’s very, very important,” she says.
Animal testing also proved very useful when it came to figuring out how to actually inject the stem cells. Emory University’s neurosurgeon Dr. Nicholas Boulis invented the device that holds the needle that injects the stem cells. The goal is to inject the cells without injuring the spine and causing even more paralysis. He practiced on 100 pigs before attempting the procedure on a human.
Boulis says it’s critical that the injection be done in a very slow and controlled way.
“If you inject quickly, you’re going to create pressure at the head of the needle and that can cause damage,” Boulis says. That pressure can also inflate an area in the spinal cord which could cause the stem cells to seep back out of the cord when the needle is pulled out, he says. “So by pumping [cells] in slowly you have more security that you are not going to have reflux and you’re not going to have damage.”
Dr. Jeffrey Rothstein, who heads the ALS research center at Johns Hopkins University and is not connected to this trial, said work on this method is a big achievement. “This is purely about how to surgically deliver cellular therapy to spinal cord,” he says. “It’s never been done before.”
After the spinal cord was exposed, the injections began. Cornick got five — each one contains about 100,000 stem cells.
The four-and-a-half hour surgery went smoothly, Boulis, says. “There were no surprises.”
A day after surgery, Cornick was lying flat in a hospital bed, chatting and laughing with some friends from North Carolina.
One week after surgery, he says he felt amazingly well and was still hopeful the cells would do some good for him.
Two weeks later Cornick’s stitches were removed and he was able to drive home. But he will be making frequent visits back to Atlanta as Glass and his team continue to monitor him.
Neuralstem’s Chief Scientific Officer Karl Johe says after the trial’s safety board reviews all existing data, including Cornick’s results, a fourth patient can be treated with the stem cells.
“Patients Four, Five and Six will receive twice as many [stem cell] injections,” Johe says. They will get five more injections on the other side of the spinal cord compared with Cornicks’s surgery.
Cornick expects the researchers will follow his progress for a long time. He says he understands the need for people to be willing to participate in experimental research like this.
“For me it just seemed like the right thing to do. I almost felt I had an obligation to do this,” he says. “To help other people and myself.”