Saturday, July 8, 2017

change disk size of VirtualBox, in osX

applejack:MacOS hqin$ VBoxManage modifyhd /Users/hqin/VirtualBox\ VMs/windows10/
Logs/                windows10.vbox       windows10.vbox-prev  windows10.vdi        
applejack:MacOS hqin$ VBoxManage modifyhd --resize 40000 /Users/hqin/VirtualBox\ VMs/windows10/windows10.vdi 
applejack:MacOS hqin$ VBoxManage showhdinfo  /Users/hqin/VirtualBox\ VMs/windows10/windows10.vdi 
UUID:           3a38dc04-987c-46be-9dda-1ded6cece216
Parent UUID:    base
State:          created
Type:           normal (base)
Location:       /Users/hqin/VirtualBox VMs/windows10/windows10.vdi
Storage format: VDI
Format variant: dynamic default
Capacity:       40000 MBytes
Size on disk:   20154 MBytes
Encryption:     disabled

In use by VMs:  windows10 (UUID: 46645298-3095-4fa0-8b95-f625b89c4b24)

Wednesday, July 5, 2017


18 pairs of students, Saturday labs.

AI and machine learning

Hologram on smart phone, tablets.

 Statement on Saturdays
 Cost for Saturdays, raspberry pi

autism, ADHD, neural diverse

Neurodiversity: autism and ADHD. Autism is an expensive diagnosis, many kids from poor family are only diagnosed with ADHD.

Hispanic family expect kids to generate income after high-schools.

school bus

Tuesday, July 4, 2017

Cancer research grand challenge

Upper  £20,000,000GBP
Each shortlisted team will be awarded up to £30,000 seed funding.

Winning teams will receive an award of up to £20 million, typically over five years.
Applicant Type
Individuals: Early Career and Emerging in Field
Individuals: Mid-Career to Established in Field
Citizenship or Residency
Activity location
Grand Challenge awards are the most ambitious cancer research grants in the world. They're intended to catalyse a revolution in how we prevent, diagnose, and treat cancer by bringing together the brightest minds around the globe, providing the freedom to undertake innovative, game-changing research.

CRUK are looking for applications from interdisciplinary teams with novel, exciting ways of solving one of seven Grand Challenges, which together encompass some of the most important unanswered questions in cancer research. If applicants can convince CRUK they're on to something extraordinary, CRUK will give the team up to £20m to prove it. Cancer Research UK is seeking scientific adventurers who are willing to take risks in exchange for the ultimate reward - making cancer a disease that no longer inspires fear.

An independent advisory panel have now set 8 new Grand Challenges and are inviting the world's top scientists to come together proposing novel ways to tackle them.

- Tissue Specificity
Devise approaches to prevent or treat cancer based on mechanisms that determine tissue specificity of some cancer genes.

- Tumour Vaccinology
Create novel tumour vaccinology approaches that establish or enhance successful immune responses beyond what is revealed by current checkpoint therapy.

- Treatment Regimens
Define mechanistic rules for combinatorial treatments to overcome resistance and avoid toxicity.

- Dormancy
Identify and target tumour cells that remain dormant for many years after seemingly effective treatment.

- Lethal vs non-lethal
Distinguish between lethal cancers which need treating, and non-lethal cancers that don't.

- Artificial Intelligence
Detect cancer earlier by interrogating medical and non-medical data sets using machine and deep-learning.

- Microbiota
Improve treatment responses by manipulating the composition and status of the microbiota.

- Cancer Causes
Determine the mechanisms that cause cancer without known mutagenesis, such as obesity, in order to devise novel interventions. 
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CRUK will support the best scientists from around the world and enable the optimal mix of disciplines and approaches. Teams are expected to be international in nature, with roughly 25% of the team being based in a different country from the rest of the consortium. There is no requirement for any of the team members to be based in the UK.

Academic-commercial collaboration is encouraged within individual Co-Investigator-led work packages.

Applicants are encouraged to consider the balance of gender and career-stage within their teams.

Teams are encouraged to look for opportunities to build patient involvement into their research. At a minimum, each team is expected to have a patient representative with a clearly defined role and remit. 
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download all file from Docscan

Turn on webserver of DocScan

This is an open access to anyone on the network.

Failed to work on osX
wget -r -np -l 1 -A zip
wget -r -l1 -H -t1 -nd -N -np -A.mp3 -erobots=off [url of website]

In virtualbox windows, use flastget3 to download all files from*

Alternatively, iTunes can import all the PDFs

wget to osX

install wget to applejack mac osX

sudo port install wget

Thursday, June 29, 2017

jet stream cloud images


The 2-micron plasmid as a nonselectable, stable, high copy number yeast vector

 1991 Mar;25(2):81-95.

The 2-micron plasmid as a nonselectable, stable, high copy number yeast vector.


The endogenous 2-microns plasmid of Saccharomyces cerevisiae has been used extensively for the construction of yeast cloning and expression plasmids because it is a native yeast plasmid that is able to be maintained stably in cells at high copy number. Almost invariably, these plasmid constructs, containing some or all 2-microns sequences, exhibit copy number levels lower than 2-microns and are maintained stably only under selective conditions. We were interested in determining if there was a means by which 2-microns could be utilized for vector construction, without forfeiting either copy number or nonselective stability. We identified sites in the 2-microns plasmid that could be used for the insertion of genetic sequences without disrupting 2-microns coding elements and then assessed subsequent plasmid constructs for stability and copy number in vivo. We demonstrate the utility of a previously described 2-microns recombination chimera, pBH-2L, for the manipulation and transformation of 2-microns as a pure yeast plasmid vector. We show that the HpaI site near the STB element in the 2-microns plasmid can be utilized to clone yeast DNA of at least 3.9 kb with no loss of plasmid stability. Additionally, the copy number of these constructs is as high as levels reported for the endogenous 2-microns.

MultiNet has lower density than CellMap genetic networks

So, MultiNet need to be re-visited.

Wednesday, June 28, 2017

yeast DIP analysis

using the 2017 data sets.  Median interactions per gene: 4, average is 8.8 for all genes.

## [1] "_explore_dip.html"  "_explore_dip.Rmd"   "Scere20170205.csv" 
## [4] "Scere20170205.txt"  "Scere20170205.xlsx"
tb = read.table("Scere20170205.txt", header=T, sep="\t", row.names=NULL)
#tb = read.xlsx("Scere20170205.xlsx", 1)
Visual check show that there are interactions between yeast proteins and non-yeast proteins (such as human and flys) Some the column names are move by one-column.
big2small = function(char1, char2) {
  if ( char1 > char2) {
    return( c( char1, char2) )
  } else {
    return( c(char2, char1) )
for( i in 1:length(tb[,1])) {
#for( i in 1:19) {
  pair = big2small(as.character(tb[i, 1]), as.character(tb[i, 2]))
  tb$pairID[i] = paste( pair[1], pair[2], sep = "::")
How many ExE interactions?
unique_EEpairs = unique(tb$pairID)
all_names = c();
for( pair in unique_EEpairs) {
  all_names = c(all_names, unlist( strsplit(pair, split="::") ))
degree = table(all_names)
##  'table' int [1:5176(1d)] 3 68 7 6 9 9 56 5 5 1 ...
##  - attr(*, "dimnames")=List of 1
##   ..$ all_names: chr [1:5176] "DIP-1000N|refseq:NP_014991|uniprotkb:P12689" "DIP-1001N|refseq:NP_010241|uniprotkb:Q07350" "DIP-1002N|refseq:NP_010206|uniprotkb:Q07468" "DIP-1003N|refseq:NP_010131|uniprotkb:P25441" ...
## [1] 8.878284
## [1] 4

order char in R

big2small = function(char1, char2) {
  if ( char1 > char2) {
    return( c( char1, char2) )
  } else {
    return( c(char2, char1) )
name1 = c("apple",  "banana", "dog", "cat")
name2 = c("banana", "apple",  "cat", "dog")
tb = cbind(name1, name2)
for( i in 1:4){
  return= big2small(tb[i, 1], tb[i, 2])
##    name2    name1 
## "banana"  "apple" 
##    name1    name2 
## "banana"  "apple" 
## name1 name2 
## "dog" "cat" 
## name2 name1 
## "dog" "cat"

set root.dir in knitr

Tuesday, June 27, 2017

AWS research grant application

AWS research grant application, receipt

yeast aging, protein biogenesis, translation control

[Janssens+Al:2015] Janssens, Georges E; Meinema, Anne C; Gonzalez, Javier; Wolters, Justina C; Schmidt, Alexander; Guryev, Victor; Bischoff, Rainer; Wit, Ernst C; Veenhoff, Liesbeth M; & Heinemann, Matthias (2015). 'Protein biogenesis machinery is a driver of replicative aging in yeast.' eLife. 4, pp. e08527.

[Blank+Al:2017] Blank, Heidi M; Perez, Ricardo; He, Chong; Maitra, Nairita; Metz, Richard; Hill, Joshua; Lin, Yuhong; Johnson, Charles D; Bankaitis, Vytas A; Kennedy, Brian K; Aramayo, Rodolfo; & Polymenis, Michael (2017). '**Translational control of lipogenic enzymes in the cell cycle of synchronous, growing yeast cells.**' *The EMBO journal*.

blackboard import packages

move course contents to another course

UTC Course merge request form

UTC Course merge request form

Google Drive install, Ubuntu Virtual machine (error)

Inside of Ubuntu virtual machine:

sudo add-apt-repository ppa:nilarimogard/webupd8
sudo apt-get update
sudo apt-get install grive
 hqin@qin2-VirtualBox:~$ sudo /usr/bin/grive
Please run grive with the "-a" option if this is the first time you're accessing your Google Drive!
hqin@qin2-VirtualBox:~$ sudo /usr/bin/grive -a 

Then copy-paste a link, loginto GoogleAcccount to get an authentication code. 

It then hangs. 

Monday, June 26, 2017

Yeast genetic map,

Three zip files
-rw-r--r--@  1 hqin  staff   497M Jun 26 09:58 Raw genetic interaction datasets- Pair-wise interaction
-rw-r--r--@  1 hqin  staff    34M Jun 26 09:58 Raw genetic interaction datasets- Matrix

-rw-r--r--@  1 hqin  staff   147M Jun 26 09:59 Genetic interaction profile similarity

Expand to three folders
drwxr-xr-x@  7 hqin  staff   238B Dec  6  2016 Data File S1. Raw genetic interaction datasets: Pair-wise interaction format
drwxr-xr-x@ 18 hqin  staff   612B Dec  6  2016 Data File S2. Raw genetic interaction datasets: Matrix format
drwxr-xr-x@  5 hqin  staff   170B Oct 20  2016 Data File S3. Genetic interaction profile similarity matrices

The global interaction dataset is based on the construction and analysis of ~23 million double mutants which identified 550,000 negative and 350,000 positive genetic interactions and covers ~90% of all yeast genes as either array and/or query mutants. The global genetic interaction dataset includes three different genetic interaction maps. First, 3,589 nonessential deletion query mutant strains were screened against the deletion mutant array covering 3,892 nonessential genes to generate a nonessential x nonessential (NxN) network. Second, 1,162 TS query mutant strains representing 804 essential genes were also screened against the nonessential deletion mutant array to generate an essential x nonessential (ExN) network. Finally, 2,241 nonessential deletion mutant query strains and 1,108 TS query mutant strains, corresponding to 795 essential genes, were crossed to an array of 792 TS strains, spanning 561 unique essential genes, to generate an expanded ExN network and an essential x essential (ExE) network. The data can be downloaded from the links below. Note that we continue to map genetic interactions for remaining gene pairs not represented in this dataset and we will update the data and networks as new interactions are generated.

Tuesday, June 20, 2017

AWS Amazon education and research grant

I used my UTC email. An verification code was sent to verify my application to AWS Educate.

AWS Cloud Credits for Research
The AWS Cloud Credits for Research program (formerly AWS Research Grants) supports researchers who seek to:
  1. Build cloud-hosted publicly available science-as-a-service applications, software, or tools to facilitate their future research and the research of their community.
  2. Perform proof of concept or benchmark tests evaluating the efficacy of moving research workloads or open data sets to the cloud.
  3. Train a broader community on the usage of cloud for research workloads via workshops or tutorials.

AWS Educate is Amazon’s global initiative to provide students and educators with the resources needed to greatly accelerate cloud-related learning endeavors and to help power the entrepreneurs, workforce, and researchers of tomorrow.


kayroplot in R,

plot along chromosome in R

UTC advising 2017-2018,

Undergraduate catalogue

College of Engineering and Computer Science

Computer Science and Engineering

Go to information for this department.



The incoming freshmen have been pre-registered in May by Laura Bass for a Fall schedule. There are several versions of a fall schedule which is based on the student’s ACT scores for their Math placement. 

The ideal schedule:
MATH 1950 – 4 hours
CPSC 1100 – 4 hours 
ENGL 1010 – 3 hours 
General Education – 3-6 Hours 

The above combination may vary for students who do not have an ACT score of 28 (and/or AP credits, joint enrolled HS credits, etc. for math courses that allow them to start in MATH 1950/Calc. I).

Students who may have an ACT score below 19 will have all Gen Ed courses scheduled for now but are being encouraged to either take the Math Dept’s Step Ahead Summer program in August for an opportunity to exit developmental Math or retake the MATH ACT residual for a higher score. If they do not exit developmental Math before classes start they will be required to take developmental Math in Fall at Chatt State or they will be very behind.