## Wednesday, July 31, 2013

### Whose notes are these?

I bought a used copy of The Biology of Life Span: A Quantitative Approach, by LA Gavrilov and NS Gavrilova. This used book contains two pages of notes. There are not many people working on the theoretic and quantitative aging modeling in the world. So, I wonder who do they belong to.

### GG91, 6.2, the need for a critical attitude to mathematical models of lifespan

GG91 discussed several instances of 'blatant errors' in 6.2.

The first is EA Murphy 1978, "Genetics of longevity in man". Murphy78 proposed a $k$ subsystems in a serial configuration, and each subsystems break down after $n$ random damages. GG91 shows an error of differentiation in the published results.

The second example is Skurnick and Kemeny, 1978, Mechanisms of Ageing and Development. SK78 argued that 'an organism' as a 'chain' whose strength is determined by the 'weakest link'. GG91 connected SK78 with the 'Bingo model'. SK78 used the extreme value distributions. SK78 inferred the Weibull model of aging and Gompertz model in old ages. GG91 stated that SK78's approximation of Gompertz model is incorrect because maximum approximation rule was used for minimum approximation. GG91 argues that this is a case that intuition and common sense would prevent such errors from happening.

The third example is Koltover 1983, Progress in Modern Biology. Koltover83 argued that death of an organism is the result of damage to at least one of the $Q$ blocks of genes in the genome. GG91 described this assumption as 'stupidity', because GG91 argued that every cell has its own genome. This critique seems to be a misplaced because K83 model can be viewed as a 'genetic interaction model', which is commonly used in evolutionary genetics.

K83 used $m_c$ for a critical value of 'disfunction' and seems to be deterministic in nature and lead to simulanenous death of a homogeneous population. K83 then introduced heterogeneity using a truncated exponential distribution to describe different populations.

The fourth example is Witten 1985, Mechanisms of Ageing and Development. GG91 shows that the derived Gompertz coefficient in W85 cannot be positive if its assumption were also positive. In other words, W85 seemed to be working on a exponential growth model if the final Gompertz derivation holds.

The first is EA Murphy 1978, "Genetics of longevity in man". Murphy78 proposed a $k$ subsystems in a serial configuration, and each subsystems break down after $n$ random damages. GG91 shows an error of differentiation in the published results.

The second example is Skurnick and Kemeny, 1978, Mechanisms of Ageing and Development. SK78 argued that 'an organism' as a 'chain' whose strength is determined by the 'weakest link'. GG91 connected SK78 with the 'Bingo model'. SK78 used the extreme value distributions. SK78 inferred the Weibull model of aging and Gompertz model in old ages. GG91 stated that SK78's approximation of Gompertz model is incorrect because maximum approximation rule was used for minimum approximation. GG91 argues that this is a case that intuition and common sense would prevent such errors from happening.

The third example is Koltover 1983, Progress in Modern Biology. Koltover83 argued that death of an organism is the result of damage to at least one of the $Q$ blocks of genes in the genome. GG91 described this assumption as 'stupidity', because GG91 argued that every cell has its own genome. This critique seems to be a misplaced because K83 model can be viewed as a 'genetic interaction model', which is commonly used in evolutionary genetics.

K83 used $m_c$ for a critical value of 'disfunction' and seems to be deterministic in nature and lead to simulanenous death of a homogeneous population. K83 then introduced heterogeneity using a truncated exponential distribution to describe different populations.

The fourth example is Witten 1985, Mechanisms of Ageing and Development. GG91 shows that the derived Gompertz coefficient in W85 cannot be positive if its assumption were also positive. In other words, W85 seemed to be working on a exponential growth model if the final Gompertz derivation holds.

## Tuesday, July 30, 2013

### Witten 1985 MAD, critical elements in a graph and Gompertz model

Witten 1985, Mech Ageing and Dev. 1985.

Witten85 used $R(t)$ as the survival function. $h_0$ as the initial mortality rate, $\gamma$ as the Gompertz coefficient. Witten85 seems to treat probability = reliability (page 142), which is different from Leemis's approach.

Witten85 assumed $m$ critical components in a graph model of a cell. There existed a critical number $m_c$ that is the threshold for the system (cell) to fail. This is equivalent to the parallel block configuration used by GG01.

Witten85 used Markov transitional states to model the failure of each critical component $M*$. I did not see how these transitional states are used for his derivation of the Gompertz model.

Witten85 used 'deviation' concept from Witten83. Witten85 assumes exponential failure function for each critical component (page 148), similar to GG01. It seems that although 'deviation' argument was used, it was not incorporated into the building toward Gompertz model.

In Eq 21, Witten85 shows that system viability (reliability) $R_SYS$ is basically the viability function of a serial system. Witten85 assumed a 'critical time' $t*$ (page 148), and approximate the binomial form in Eq 21 to obtain the Gompertz form using the exactly approximation used by GG91.

It is perplexing to me that Eq21 shows a serial configuration (based on Eq 14), but Witten85 argues for parallel configuration in Eq 13. For serial system, the product form also means that any single failure of the critical components will lead to system failure. If 'all of the critical elements must fail' for a system to fail, it should be a parallel configuration.

Witten85 introduced 'cost' in Eq 30 on page 152: Cost ~ m^beta, where $m$ is the number of critical elements.

Witten85 used $R(t)$ as the survival function. $h_0$ as the initial mortality rate, $\gamma$ as the Gompertz coefficient. Witten85 seems to treat probability = reliability (page 142), which is different from Leemis's approach.

Witten85 assumed $m$ critical components in a graph model of a cell. There existed a critical number $m_c$ that is the threshold for the system (cell) to fail. This is equivalent to the parallel block configuration used by GG01.

Witten85 used Markov transitional states to model the failure of each critical component $M*$. I did not see how these transitional states are used for his derivation of the Gompertz model.

Witten85 used 'deviation' concept from Witten83. Witten85 assumes exponential failure function for each critical component (page 148), similar to GG01. It seems that although 'deviation' argument was used, it was not incorporated into the building toward Gompertz model.

In Eq 21, Witten85 shows that system viability (reliability) $R_SYS$ is basically the viability function of a serial system. Witten85 assumed a 'critical time' $t*$ (page 148), and approximate the binomial form in Eq 21 to obtain the Gompertz form using the exactly approximation used by GG91.

It is perplexing to me that Eq21 shows a serial configuration (based on Eq 14), but Witten85 argues for parallel configuration in Eq 13. For serial system, the product form also means that any single failure of the critical components will lead to system failure. If 'all of the critical elements must fail' for a system to fail, it should be a parallel configuration.

Witten85 introduced 'cost' in Eq 30 on page 152: Cost ~ m^beta, where $m$ is the number of critical elements.

### Witten 1983, MAD,

Witten83MAD argues for a systems approach and argues that a 'local model' is need for mechanistic insights.

Its aging model in linear form is:

Its threshold-like aging model is:

Witten83 then use mortality rate and survival function to find a probability density function, called a "general form of mortality" (page 75). Witten83 parametrized $\alpha_R(t)$ for detailed studies.

Without loss of generality, let us consider a single cell as our system of interest. When a new cell comes into being, it must function in some "average normal" manner (we'll assume that we are examining normal cells). In order for a cell to function in this "average normal manner" it must have some idea of what functions it must perform. That is to say, if it is a pancreatic islet cell then it must do all those things a "normal" pancreatic islet cell must do. This knowledge must be abstractly embedded in the cell as programming an internal model/rules and laws - whatever you choose. In brief, the cell has a set of internal perceptions as to what its normal function in a normal environment must be. (page 71, Witten83MAD).

If, as clock time passes, the cell's external environment changes in some substantialWitten83 use $R_SYS$ as survival function, and $\lambda$ as mortality rate. Witten83 formulated the normal deviation $\alpha_N$ and aging devivation $\alpha_R(t)".

manner, then thedeviation between the cell's programmed picture of the normal world environment and the real world environmentbecomes quite large. The consequence of this deviation could well be the development of reversible and non-reversible agerelated effects. In the following paragraphs, we investigate how these concepts may be formalized. This will lead us toa definition of senescence in terms of these deviations. (page 72).

Its aging model in linear form is:

Its threshold-like aging model is:

Witten83 then use mortality rate and survival function to find a probability density function, called a "general form of mortality" (page 75). Witten83 parametrized $\alpha_R(t)$ for detailed studies.

### Talk with Lou, exit interview

Lou came to my office and talked with me for about 40 minutes. Lou mentioned that new MCAT will emphasize more on statistics.

### Fastlane tips

https://www.fastlane.nsf.gov/NSFHelp/flashhelp/fastlane/FastLane_Help/prepare_a_new_notification_or_request_as_a_pi.htm

I followed the above instruction, filed an

**"**NSF Approved No-Cost Extension", in order to use the residual fund to cover the registration cost for a September meeting.

Note: Change of closing date should be filed 45 days in advance.

## Monday, July 29, 2013

### PubMed to BibTex

1. BibDesk through HubMed

BibDesk seems to run on Mac, Windows, and Linux.

2. Texmed

http://www.bioinformatics.org/texmed/

Copy-past from TexMed to *.bib files include "quotes". So, I have manually add the fields in BibDesk.

BibDesk seems to run on Mac, Windows, and Linux.

2. Texmed

http://www.bioinformatics.org/texmed/

Copy-past from TexMed to *.bib files include "quotes". So, I have manually add the fields in BibDesk.

### Comparison of mortality rates, human, medflies, fruit flies, worms, yeast and automobiles, Vaupel et al. 1998 Science

Vaupel et al. 1998 Science plotted the death rate (mortality rate) for human, medflies, wasps, fruit flies, worms, yeast, and automobiles in its Figure 3. The plot on human was zoomed in to between age 80 and 120, because the Vaupel98Sci seem to emphasize the late life differences.

A Scholar search shows many engineering hits on automobile and Weibull modeling.

A Scholar search shows many engineering hits on automobile and Weibull modeling.

## Sunday, July 28, 2013

### Feynman's comment on experimental skill and openning toothpaste tube.

This is a good example of edutainment. I should edit a video on this topic.

See:

http://blogs.scientificamerican.com/oscillator/2013/07/27/feynman-on-biology/

There was one useful lab technique I learned in that course which I still use today. They taught us how to hold a test tube and take its cap off with one hand (you use your middle and index fingers), while leaving the other hand free to do something else (like hold a pipette that you’re sucking cyanide up into). Now I can hold my toothbrush in one hand, and with the other hand, hold the tube of toothpaste, twist the cap off, and put it back on. (From Surely You're Joking, Mr. Feynman).

See:

http://blogs.scientificamerican.com/oscillator/2013/07/27/feynman-on-biology/

## Friday, July 26, 2013

### Baudisch 2011 Methods in Ecology and Evolution, The pace and shape of ageing

Baudisch 2011, The pace and shape of ageing.

Baudisch11 standardized survive curves by normalizing age by its own expectation: x / E[x] . This is a very good idea and can be used to compare survive curves in different species with different time scale. For my work, it makes comparing yeast replicative and chronological lifespan possible.

Baudisch11 argues that 'shape' is a unit-less measure, and 'pace' is basically 'rate' with unit 1/time.

Shape measures discussed are:

Omega/L (Omega is age at 1% viability, and L is the average age).

mu(Omega) / mu(0) or \bar{mu}

mu(L)/mu(0) or \bar{mu}

Pace measures argued by Baudisch11 seem to include the two canonical Gompertz parameters.

In its Figure 3, L, Omega, and Maturity seem to be considered as 'pace' measures, too.

Baudisch11 uses 'mortality' for 'mortality rate', which can be seen in her description of the Gompertz model.

Baudisch11 discussed a measure proposed by Ricklef1998 and argued that it is problematic.

It can be seen that x/E[x] is unitless. So, Baudisch11 approach is a nondimensionalization treatment.

Baudisch11 discussed some previous work on dimensionless analysis of aging: Pearl and Miner 1935, Eakin 1994.

Numerically, it is straightforward to calculate the 'shape' measures. However, it is not straightforward to find the analytic form of the shape measures based on the Gompertz or Weibull models.

The median lifespan, i.e., the 50% quantile, has a analytic solution. So, normalization by the median lifespan can be used for both theoretical and empirical analysis.

Baudisch11 standardized survive curves by normalizing age by its own expectation: x / E[x] . This is a very good idea and can be used to compare survive curves in different species with different time scale. For my work, it makes comparing yeast replicative and chronological lifespan possible.

Baudisch11 argues that 'shape' is a unit-less measure, and 'pace' is basically 'rate' with unit 1/time.

Shape measures discussed are:

Omega/L (Omega is age at 1% viability, and L is the average age).

mu(Omega) / mu(0) or \bar{mu}

mu(L)/mu(0) or \bar{mu}

Pace measures argued by Baudisch11 seem to include the two canonical Gompertz parameters.

In its Figure 3, L, Omega, and Maturity seem to be considered as 'pace' measures, too.

Baudisch11 uses 'mortality' for 'mortality rate', which can be seen in her description of the Gompertz model.

Baudisch11 discussed a measure proposed by Ricklef1998 and argued that it is problematic.

It can be seen that x/E[x] is unitless. So, Baudisch11 approach is a nondimensionalization treatment.

Baudisch11 discussed some previous work on dimensionless analysis of aging: Pearl and Miner 1935, Eakin 1994.

Numerically, it is straightforward to calculate the 'shape' measures. However, it is not straightforward to find the analytic form of the shape measures based on the Gompertz or Weibull models.

The median lifespan, i.e., the 50% quantile, has a analytic solution. So, normalization by the median lifespan can be used for both theoretical and empirical analysis.

### Baudisch & Vaupel, 2012, Science, Getting to the root of aging.

"Getting to the root of aging", Annette Baudisch, James Vaupel, 2012 Science.

BV12 focused on the three patterns of aging in biology: 1) Increasing mortality rate over age in human, mammals and birds; 2) Flat mortality rate over age in freshwater polyp Hydra vulgaris; 3) Decreasing mortality rate over age in tortoise Gopherus agassizii and many reptiles, amphibians, fish, and plants.

BV12 discussed Baudisch12Gerontology, where Baudisch discussed various models. It was mentioned that enhanced repair and maintenance can lead to flat or decreasing mortality rate over age. Increasing reproductive potential with age was also mentioned.

Estep 2010 argues that decline asexual reproduction is an indicator of senescence in hydra.

I thought a plausible way to explain the decreasing mortality rate in tortise is to use the parasites or viruses argument: older individuals are more resistant to pathogens.

I had a discussion with Adam Reitzel, UNC Charlotte about hydra aging at SMBE2013. We discussed whether hydra has an more active repair/renewal mechanism than other organisms. This lead me to wonder about the aging pattern in planarian

References:

Turner FB, Berry KH, Randall DC, White GC. Report No. 87-RD-81”. Southern California Edison Company; 1987. “Population ecology of the desert tortoise at Goffs, California, 1983-1986.

(I did not find online sources for this reference).

MartΓnez DE. Exp. Gerontol. 1998;33:217

BV12 focused on the three patterns of aging in biology: 1) Increasing mortality rate over age in human, mammals and birds; 2) Flat mortality rate over age in freshwater polyp Hydra vulgaris; 3) Decreasing mortality rate over age in tortoise Gopherus agassizii and many reptiles, amphibians, fish, and plants.

BV12 discussed Baudisch12Gerontology, where Baudisch discussed various models. It was mentioned that enhanced repair and maintenance can lead to flat or decreasing mortality rate over age. Increasing reproductive potential with age was also mentioned.

Estep 2010 argues that decline asexual reproduction is an indicator of senescence in hydra.

I thought a plausible way to explain the decreasing mortality rate in tortise is to use the parasites or viruses argument: older individuals are more resistant to pathogens.

I had a discussion with Adam Reitzel, UNC Charlotte about hydra aging at SMBE2013. We discussed whether hydra has an more active repair/renewal mechanism than other organisms. This lead me to wonder about the aging pattern in planarian

*.*I found one article, Mouton11, that reported lack of metabolic aging in Schmidtea polychora.References:

Turner FB, Berry KH, Randall DC, White GC. Report No. 87-RD-81”. Southern California Edison Company; 1987. “Population ecology of the desert tortoise at Goffs, California, 1983-1986.

(I did not find online sources for this reference).

MartΓnez DE. Exp. Gerontol. 1998;33:217

Estep, Exp Gerontol. 2010 Sep;45(9):645-6. doi: 10.1016/j.exger.2010.03.017. mm

Declining asexual reproduction is suggestive of senescence in hydra: comment on Martinez, D., "Mortality patterns suggest lack of senescence in hydra." Exp Gerontol 33, 217-25

Mouton S, Willems M, Houthoofd W, Bert W, Braeckman BP. Exp Gerontol. 2011 Sep;46(9):755-61. doi: 10.1016/j.exger.2011.04.003. Epub 2011 Apr 23. Lack of metabolic ageing in the long-lived flatworm Schmidtea polychroa.

Declining asexual reproduction is suggestive of senescence in hydra: comment on Martinez, D., "Mortality patterns suggest lack of senescence in hydra." Exp Gerontol 33, 217-25

Mouton S, Willems M, Houthoofd W, Bert W, Braeckman BP. Exp Gerontol. 2011 Sep;46(9):755-61. doi: 10.1016/j.exger.2011.04.003. Epub 2011 Apr 23. Lack of metabolic ageing in the long-lived flatworm Schmidtea polychroa.

## Thursday, July 25, 2013

### Six degree of separation based on random graph, Watts and Strogatz ln V/ lnK

Based on Wikipedia entry, Watts and Strogatz showed that average path length between two nodes in a random network is lnV/lnK, where V is the number of node, and K is the average degree.

So, ln 6.7 billion / ln (50 friends) = 5.7.

See also:

https://en.wikipedia.org/wiki/Six_degrees_of_separation#Research

So, ln 6.7 billion / ln (50 friends) = 5.7.

See also:

https://en.wikipedia.org/wiki/Six_degrees_of_separation#Research

## Tuesday, July 23, 2013

### GitHub for ORAU R tutorial

Create ORAU-R on GitHub website.

https://github.com/hongqin/ORAU-R

Locally,

**$ cd /Users/hongqin/github/ORAU-R**

**$ git init**

**Initialized empty Git repository in /Users/hongqin/dropbox/courses.student.research.dp/ORAU-R/.git/**

**$ git add ***

**$ git remote add origin https://github.com/hongqin/ORAU-R.git**

**$ git push --force origin master**

**$**

**git config http.postBuffer 209715200**

**Username for 'https://github.com': hongqin**

**Password for 'https://hongqin@github.com':**

**Counting objects: 76, done.**

**Delta compression using up to 2 threads.**

**Compressing objects: 100% (76/76), done.**

**Writing objects: 100% (76/76), 11.67 MiB | 4.30 MiB/s, done.**

**Total 76 (delta 6), reused 0 (delta 0)**

**To https://github.com/hongqin/ORAU-R.git**

**+ d602d3b...260adfb master -> master (forced update)**

### Positive feedback, bistability, and pattern formation

Positive feedback loops can be used to model emergent ecological patterns, such as Alpine tree lines, based on discussion with JJ at NIMBioS.

## Monday, July 22, 2013

### R tutorial for Oak Ridge Science Education

Please note that the entire workshop material can be download from its GitHub repository ORAU-R.

## 1.What is R?

Wikipedia entry on RWhy R by Courtney Brown at Emory.

Why R and beyond.

R blogger that provides recent and often interesting development about R.

What is R video (Added after the class).

## 2. Install R to your own computers.

Instructions to download R.Install R studio. RStudio provides a nice GUI to R.

Install packages to R: Video for Windows Version.

## 3. Introduction to R.

Hong Qin's slides: Overview of R; Basic programming in R; Input & Output in R;

Lydon Walker, getting started with R, an accelerated primer

## 4. Simple exercises in R.

Qin's simple.R excises. Please select 'Raw' and 'save-as' in text format. Unfortunately, web browser seem to automatically add 'txt' to the file name, and Rstudio does not run 'txt' format. To solve this problem, we can 'create' a new R script, and copy-paste from code from the text file.

(The workshop audience mostly reached this step).

Youtube tutorial converting Excel data to CSV and load into R.

The sunflow seed Excel file is here.

##

##

Write an R function to calculate how much NaCl needed for X ml of Y mM NaCl solution.

Simple regression exercise.

(The workshop audience mostly reached this step).

Youtube tutorial converting Excel data to CSV and load into R.

The sunflow seed Excel file is here.

## 5. Make solution exercise.

## 6. Simple statistical analysis in R.

## 7. Advanced training materials.

Multiple regression demo

Hierarchical clustering using cities. Code, Video.

Laddy Gaga and clustering analysis. Code. Video.

Bioconductor workshop materials.

Hierarchical clustering using cities. Code, Video.

Laddy Gaga and clustering analysis. Code. Video.

- Stephen J. Eglen's PLOS article. A quick guide to teaching R programming to computational biology students.

http://addictedtor.free.fr/graphiques/.

Newly launched interactive cloud-based R for teaching: http://www.datamind.org/

Google-developers R programming videos

Avril Coghlan's little book of R for bioinformatics.

Github's collection of free R books

R by examples

## 9. Discussions on programming workshops.

Titus Brown's blog on teaching programming.## 10. My reflections

The main workshop is led by Jame Ferguson and Bob Panoff. There were 9 college biology and 2 high-school biology faculty in the workshop.I was given 90 minutes. My goal was that audience would be able to install R and Rstudio and run R scripts on their own after the workshop.

I spent 30 minutes on introducing R to the audience, my experience of teaching R and computational genomics to undergraduates. I showed them the GEO database and R interface. I used the examples of make-solution, hclust on cities and Lady Gaga. For the next 50 minutes, I let the audience to download and install Rstudio. A few of them needed my help to down and install R and Rstudio. Most of them were able to run to the simple.R exercise (step 4.a). I run out of time after step 6.

I was somewhat stunned that downloading R code directly from GitHub repository is surprisingly cumbersome.

During the exercise time, a few people were clearly ahead and poked around. Some were especially interested in the GEO2R portal.

Bob mentioned that R has been used in a few other liberal art colleges, including Davidson and Pomona.

At the end of the workshop, I was asked "why do 'we' have to teach R to biology students?". I used my own experiences and argued that R is the state-of-the-art tool for data analysis in biology.

**For preparation for the workshop**

Wireless connection, laptops, power-outlets are recommended.

Install packages and data on flash-drives in case internet connection is slow. (This can be a problem when all participants are download at the same time.)

A flow-chart on easel can be used for clarity.

### Install R to your own computers.

####
- Go to http://cran.r-project.org/ , select the binary version for your computer.

- Select the lastest 'base' version.

## Monday, July 15, 2013

### Evolution did not select for long lifespan

Some gene deletions lead to longer lifespan, which argues that evolution did not selection for individual long lifespan. Evolution general select for better fitness. This means that different models of viability and fitness may have different evolutionary consequences. For example, linear form between viability and fitness versus exponential form?

There must be a lot of publication on this topic that I need to find out.

There must be a lot of publication on this topic that I need to find out.

## Sunday, July 14, 2013

### Aging, essentiality, and the evolution of non-essentiality (robustness).

In many cellular organisms, genes can be either essential or non-essential. It seems obvious for people to argue for the origin of essentiality. From the network work aging perspective, the non-essential genes actually are the key for the characteristics of biological aging. The exponential viability curves of viruses suggest that every viral gene is essential. Hence, evolutionary transition from simple viruses to cellular organisms is to add non-essential genes, because essentiality predates the cellular life. Presumably, essentiality exists in the RNA world. It is the non-essential genes that give redundancy and robustness to gene networks which manifested themselves as the increasing mortality rate over time. Hence, the non-essential genes play much larger roles than essential genes with regards to diversity and innovations. In a way, this argument is related to Ohno's duplication argument.

## Saturday, July 13, 2013

## Friday, July 12, 2013

### systems biology makeup language, VPLAN

*systems biology makeup language xml format is used by Tobias Meyer VPLAN

## Tuesday, July 9, 2013

### Note, CH Langley nucleosome structure

CH Langley: Dinucleotid frequencies in D. melanogster genome show 10bp periodicity.

Related paper:

Repoertories of the nucleosome-positioning dinucleotides, Thomas Bettecken, Edward N. Trifonov,

http://www.plosone.org/article/info:doi/10.1371/journal.pone.0007654

Related paper:

Repoertories of the nucleosome-positioning dinucleotides, Thomas Bettecken, Edward N. Trifonov,

http://www.plosone.org/article/info:doi/10.1371/journal.pone.0007654

### DNA content, rDNA cluster size detection by flow cytometer

Marcus Nordberg used flow cytometer to detect genome size variation. He thought genome variation is primarily due to rDNA cluster size changes. In yeast, rDNA cluster size -> translational speed and accuracy OR extra-chromosomal rDNA circles OR genomic instability. rDNA and ribosomal function is related to lifespan. So, flow cytometer can be used to quickly phenotype rDNA sizes.

Alternatively, qPCR, short-reads mapping, and southern hybridization can be used. In this case, standardized rDNA clusters will be used to generate a standard curve. The rDNA cluster reference strains are available in David Bedwell's lab at UAB.

Alternatively, qPCR, short-reads mapping, and southern hybridization can be used. In this case, standardized rDNA clusters will be used to generate a standard curve. The rDNA cluster reference strains are available in David Bedwell's lab at UAB.

## Monday, July 8, 2013

### Forbidden interaction and aging

Joshua Rest argues that forbidden interactions are deleterous, and may occur more often in aging due to disregulated expressions. JRest suggests to introduce gain of interaction during aging.

JRest' idea is simliar to snowball model, in retrospect.

JRest' idea is simliar to snowball model, in retrospect.

### Ribosomal fidelity, translational rate, network reliability, and transcriptional fidelity

Someone mentioned that there is tradeoff between translation accuracy and speed. If translational accuracy leads to reliability change in general, it has global effect on function decay rate in my network aging model. This may be used to model the ribosomal effect on lifespan.

This argument would suggests that codon bias is related to network reliability and aging. So, codon bias modification may influence aging dynamics? Can better codon bias lead to long lifespan, smaller m0 and large G (more homogeneity)?

The mRNA ribosomal profiling is a measure of translation activity.

In E coli, slow translation is found when ribosomal proofreading is more active.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC557732/

http://www.sciencedirect.com/science/article/pii/S0968000400017370

Wuttle12 proposed a meiosis-related rejuvenation process for CR.

slow growth and high protein fidelity?

rpl20b: null leads to slow vegetative growth

ndt80

tor1

sch9

July 15, 2015:

transcriptional fidelity?

http://www.ncbi.nlm.nih.gov/pubmed/26159996

August 13, 2015 rogue ribosome translation

http://phys.org/news/2015-08-biologists-ribosomes-untranslated-region-messenger.html

This argument would suggests that codon bias is related to network reliability and aging. So, codon bias modification may influence aging dynamics? Can better codon bias lead to long lifespan, smaller m0 and large G (more homogeneity)?

The mRNA ribosomal profiling is a measure of translation activity.

In E coli, slow translation is found when ribosomal proofreading is more active.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC557732/

http://www.sciencedirect.com/science/article/pii/S0968000400017370

Wuttle12 proposed a meiosis-related rejuvenation process for CR.

slow growth and high protein fidelity?

rpl20b: null leads to slow vegetative growth

ndt80

tor1

sch9

July 15, 2015:

transcriptional fidelity?

http://www.ncbi.nlm.nih.gov/pubmed/26159996

August 13, 2015 rogue ribosome translation

http://phys.org/news/2015-08-biologists-ribosomes-untranslated-region-messenger.html

Labels:
***,
codon bias,
CR,
ideas,
network aging,
proposal,
qin,
star,
translation

## Wednesday, July 3, 2013

### cellular potts model and quorem sensing

cellular potts model and quorem sensing, antibiotic persistence

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