This site is to serve as my note-book and to effectively communicate with my students and collaborators. Every now and then, a blog may be of interest to other researchers or teachers. Views in this blog are my own. All rights of research results and findings on this blog are reserved. See also http://youtube.com/c/hongqin @hongqin
Wednesday, October 29, 2014
bio386, 2014Oct29. Practice presentation of robustness poster
Practice presentation of the poster on robustness.
Tuesday, October 28, 2014
BIO233, Tue 20141028, R and Rstudio, anonymous comments
I let students work on R and Rstudio to do data analysis.
At the end of the class, I ask student to write anonymous notes. The comments are generally positive. Several students ask for review of questions and topics in exam and assignments.
Some student did appreciate the Excel worksheet study on LOH. Maybe I should be more explicit on the LOH and aging.
At the end of the class, I ask student to write anonymous notes. The comments are generally positive. Several students ask for review of questions and topics in exam and assignments.
Some student did appreciate the Excel worksheet study on LOH. Maybe I should be more explicit on the LOH and aging.
mathramp, 2014 Oct 28
Rstudio was not moved into "Application".
Went over R code for simulating aging in permuted networks.
Went over R code for generating histogram of CV
Monday, October 27, 2014
bio233 lab, R and Rstudio analyze of serial dilution data
We spent about 1 hour install R and Rstudio. I then told many students to work as a team.
Some students have various windows computers, and their interface were different.
Then many students waited for xlsx package to be installed through wireless. I have to abadon the xlsx approach, and switched to csv approach.
I then let students reviewed their streaked plates. Only 1 plate can be given A-. The rest of them are at B- . About 2/3 of the plates have to be redone (below C).
I let the students try to streak the plates again. Next day, I found out that almost all students failed. Most students seem to pick the old colonies for every streak, meaning that they did not get the idea at all.
Some students tried to open R code in the ZIP archive directly. This is a common mistake. This problem become more annoying with the different version of operating systems offer different viewing and extraction options.
Some students have various windows computers, and their interface were different.
Then many students waited for xlsx package to be installed through wireless. I have to abadon the xlsx approach, and switched to csv approach.
I then let students reviewed their streaked plates. Only 1 plate can be given A-. The rest of them are at B- . About 2/3 of the plates have to be redone (below C).
I let the students try to streak the plates again. Next day, I found out that almost all students failed. Most students seem to pick the old colonies for every streak, meaning that they did not get the idea at all.
Some students tried to open R code in the ZIP archive directly. This is a common mistake. This problem become more annoying with the different version of operating systems offer different viewing and extraction options.
Friday, October 24, 2014
R code for midterm grade report
#require(xlsx)
rm(list=ls())
list.files()
tb = read.csv("some grades.csv")
empty.columns= NULL
for (j in 8:length(tb[1,])){
#for( i in 1:length(tb[,1])){
# if( tb[i,j]=='-') {tb[i,j]=NA }
#}
tb[,j] = as.numeric( tb[,j])
tb[is.na(tb[,j]),j] = 0
if( max(tb[,j])==0 ) { empty.columns = c(empty.columns, j)}
}
str(tb)
tb2 = tb[, - empty.columns]
#tb2 = tb2[, -"Course.total"]
#tb2 = tb2[, - grep('Spring', names(tb2))]
#tb2 = tb2[, - grep('spring', names(tb2))]
tb2 = tb2[, -grep("Quiz.Retake..Fall.2014.Exam.1..part.2..online.part", names(tb2))]
names(tb2)
exam1 = c("Quiz.Exam1.Part1..Fall.2014" ,
"Assignment.exam1..part2..calculation.questions..fall.2014",
"Quiz.Fall.2014.Exam.1..part.2..online.part" )
exam2= c("Quiz.Exam.2..closed.book.section..Fall.2014..Thursday",
"Quiz.Exam2..open.book.section..Fall.2014..Tuesday")
report= tb2[,1:2]
report$Exam1 = apply( tb2[,exam1], 1, sum)
report$Exam2 = apply( tb2[,exam2], 1, sum)
practical = "Assignment.Practical.Exam..microscope.and.morphology..Sep.29..2014"
report$practical = tb2[,practical]/20
scale = c("Quiz.Lab.assignment..Scale.of.Microbes",
"Quiz.scale.of.microbes..lab.report")
report$scale= apply( tb2[, scale],1, max)
misc= c("Quiz.DePaepeTaddei.Reading.Assignment" ,
"Quiz.Lab.assignment..E.coli.genome.studies")
tb2[1:5, misc]
report$misc= apply( tb2[, misc],1, sum)
report$ch1 = tb2[, grep("Chapter.1",names(tb2))]
report$ch2 = tb2[, grep("chapter.2",names(tb2))]
report$ch3= apply( tb2[, grep("Chapter.3",names(tb2))],1, max)
report$ch4= apply( tb2[, grep("Chapter.4",names(tb2))],1, max)
report$ch5= apply( tb2[, grep("Chapter.5",names(tb2))],1, max)
report$ch5= apply( tb2[, grep("ch6",names(tb2))],1, max)
report$ch7= apply( tb2[, grep("ch7",names(tb2))],1, max)
report$ch8= apply( tb2[, grep("ch8",names(tb2))],1, max)
names(tb2)[grep("Quiz", names(tb2))]
assignAndLab =c("scale","misc","ch1","ch2","ch3","ch4","ch5","ch7","ch8")
report$assignAndLab = apply( report[,assignAndLab], 1, sum)
maxS = apply( report[, assignAndLab], 2, max)
report$assignAndLab = 15*report$assignAndLab / sum(maxS)
report$highExam = apply(report[,c("Exam1","Exam2")], 1, max)
head(report)
midterm= c("highExam","practical","assignAndLab")
report$midterm= apply(report[,midterm], 1, sum) *100/70
head(report[,midterm])
hist( report$midterm )
grade2letter = function(x){
if(x>94){ ret='A'
}else if (x >90) { ret='A-'
}else if (x >87 ){ ret = 'B+'
}else if (x > 84){ ret = 'B'
}else if (x >80){ ret = 'B-'
}else if (x > 76){ ret = 'C+'
}else if (x > 70){ ret = 'C'
}else if (x > 67){ ret = 'C-'
}else if (x > 64){ ret = 'D+'
}else if (x > 60){ ret = 'D'
}else { ret = 'F'
}
return (ret)
}
grade2letter(70); grade2letter(88)
report$letter = lapply(report$midterm, grade2letter)
Wednesday, October 22, 2014
bio386 20141022 Wed t-test, constructive learning
The students were guided to learn the meaning of p-value and t-test.
They spent about 1 hour on the t-test.R example, and figured out small p-value means 'null hypothesis is disproved'.
I then tried to see whether they can apply their newly learned knowledge in the metric-survey data set. The students have trouble to state the null hypothesis for the metric_v2b.R
t.test(tb2$metric[tb2$gender=='Female'], tb2$metric[tb2$gender=='Male'])
At this time, we reach the end of class, so I left this as homework.
They spent about 1 hour on the t-test.R example, and figured out small p-value means 'null hypothesis is disproved'.
I then tried to see whether they can apply their newly learned knowledge in the metric-survey data set. The students have trouble to state the null hypothesis for the metric_v2b.R
t.test(tb2$metric[tb2$gender=='Female'], tb2$metric[tb2$gender=='Male'])
At this time, we reach the end of class, so I left this as homework.
Fastlane submit a revised budget
Access the Proposal Revised Budget Screen
- 1. On the FastLane Home Page screen, log in as a PI to Proposals, Awards, and Status (see PI/Co-PI Login). The Principal Investigator (PI)/Co-Principal Investigator (Co-PI) Management screen displays (Figure 1).
Figure 1 Principal Investigator (PI)/Co-Principal Investigator (Co-PI) Management screen. The Proposal Functions link is circled.
- 2. Click Proposal Functions (Figure 1). The Principal Investigator (PI)/Co-Principal Investigator (Co-PI) Management Proposal Functions screen displays (Figure 2).
Figure 2 Principal Investigator (PI)/Co-Principal Investigator (Co-PI) Management Proposal Functions screen. The Revise Submitted Proposal Budget link is circled.
- 3. Click Revise Submitted Proposal Budget (Figure 2).
Figure 3 List of Proposals screen. The View button is circled.
- 4. Highlight the proposal whose budget you want to revise from the List of Proposals (Figure 3).
5. Click the View button (Figure 3). The Proposal Revised Budget screen displays (Figure 4) with the following options:
- • View the budget
• Edit the budget
• Refresh to the last submitted budget
• Assign a PIN to the Revised Proposal Budget
• Forward a Revised Proposal Budget to the Sponsored Project Office (SPO)
• Add/Delete Senior Personnel
(Click on a link above for instructions for that action.)
Figure 4 Proposal Revised Budget screen.
Edit the Submitted Budget
- 1. Access the Proposal Revised Budget screen (Figure 1) (see Access the Proposal Revised Budget Screen).
Figure 1 Proposal Revised Budget screen. The radio button for Edit the Budget and the OK button are circled.
- 2. Click the radio button for Edit the Budget (Figure 1).
3. Click the OK button (Figure 1). The Project Budget screen displays (Figure 2). For instructions for editing any budget year, see Budgets (Including Justification) and Enter the Budget Data Online.
Figure 2 Project Budget screen.
Once you have calculated and saved the edited budget, it is listed as the Working Budget on the View/Print Revised Budget(s)screen (Figure 3).
Figure 3 View/Print Revised Budget(s) screen with the new Revised Proposal Budget now listed as the WorkingBudget (circled).
Tuesday, October 21, 2014
bio233 exam 2 open book online quiz
In the current Moodle system, when essay questions are not graded, the final grade is shown as "not yet graded".
"Mark" shown seem to give hints to students.
"Mark" shown seem to give hints to students.
Monday, October 20, 2014
bio233, counting sectioned colonies for serial dilution lab
I took pictures of the MLA plates.
Students were given 3 marker pens with different colors and a tally to count colonies. Many students ask for more tallies. (I need to order more tallies next time).
Many students for some reasons did not input their data to GoogleDoc spread sheets. It seemed that some wrote in their notebook or just some piece of paper that were available to them. The counting and calculation took more than 2 hours.
I did not have time to merge the data and do regression analysis. I showed some students how to install R and Rstudio. The wireless connection took a long time for some student download R and Rstudio.
Students were given 3 marker pens with different colors and a tally to count colonies. Many students ask for more tallies. (I need to order more tallies next time).
Many students for some reasons did not input their data to GoogleDoc spread sheets. It seemed that some wrote in their notebook or just some piece of paper that were available to them. The counting and calculation took more than 2 hours.
I did not have time to merge the data and do regression analysis. I showed some students how to install R and Rstudio. The wireless connection took a long time for some student download R and Rstudio.
Install R and Rstudio on Windows and Mac computers
1. Install R (This is the main computing and programming engine).
1.1 Go to:
http://mirrors.nics.utk.edu/cran/
1.2 Pick the right R version for your computer platform.
For Mac OS X users, you need to identify the version of your system and download the right one.
2. Install Rstudio (This is the user-friendly editor and environment to run R).
http://www.rstudio.com/products/rstudio/download/
Note: Rstudio must be installed after installation of R.
Video:
Install R and Rstudio on Windows computers
http://youtu.be/eD07NznguA4
Install R and Rstudio on Mac computers
http://youtu.be/Ywj6yNfc5nM
Friday, October 17, 2014
bio386 R learning, apply, margin, t-test, p-value
I let students first reviewed R code 1-100 lines.
Then, student worked through 100-165.
I asked student to study examples of 'apply' and "margin". I then used a table on a paper to explain this. (I could do a youtube demo on this).
When we reached t-test and p-value, students have mis-conceptions. One student thought "as close to the one" means p-value should be close to 1 from the wikipedia entry on p-value.
Then, student worked through 100-165.
I asked student to study examples of 'apply' and "margin". I then used a table on a paper to explain this. (I could do a youtube demo on this).
When we reached t-test and p-value, students have mis-conceptions. One student thought "as close to the one" means p-value should be close to 1 from the wikipedia entry on p-value.
Thursday, October 16, 2014
bio233 exam 2 review
I gave out previous questions and worked through them in class.
I also handout some MCAT prep questions on paper.
Time runs out pretty fast. I finished less than 10 questions in class.
I also handout some MCAT prep questions on paper.
Time runs out pretty fast. I finished less than 10 questions in class.
Wednesday, October 15, 2014
Tuesday, October 14, 2014
MG149, histone acetyltransferase inhibitor
MG149 is a potent histone acetyltransferase inhibitor with IC50 of 74 μM and 47 μM for Tip60 and MOF,respectively.
http://www.selleckchem.com/products/mg149.html
I am not sure whether MG149 is related to aging or not at the moment.
http://www.selleckchem.com/products/mg149.html
I am not sure whether MG149 is related to aging or not at the moment.
Saturday, October 11, 2014
SURA meeting 20141010
XSEDE educational meeting, DC.
SURA president is a nuclear physicist.
Changing curriculum is like moving a cemetery.
I am computational and mathematical biologist, statistical geneticist and biophysicist
faculty advisor for Spelman SIAM Chapter
I student gene network and genomics,
network aging,
computing intensive, 2 days for one run.
R
bioinformatics/systems biology minor
computational genomics
microbiology
molecular biology
Python and bioinformatics programming
8 courses
Nathan Bowen, CAU
bowen at cau.edu
404 880 8158
Why Pringles Fly?
Accepting the idea of computational education is accepted.
Seismic data and image computing, simulation, subsurface
Can major courses also be used for minor requirement?
stake-holders
Culture change, faculty training,
Scholarship
MCAT
SURA president is a nuclear physicist.
Changing curriculum is like moving a cemetery.
I am computational and mathematical biologist, statistical geneticist and biophysicist
faculty advisor for Spelman SIAM Chapter
I student gene network and genomics,
network aging,
computing intensive, 2 days for one run.
R
bioinformatics/systems biology minor
computational genomics
microbiology
molecular biology
Python and bioinformatics programming
8 courses
Nathan Bowen, CAU
bowen at cau.edu
404 880 8158
Why Pringles Fly?
Accepting the idea of computational education is accepted.
Seismic data and image computing, simulation, subsurface
Can major courses also be used for minor requirement?
stake-holders
Culture change, faculty training,
Scholarship
MCAT
Wednesday, October 8, 2014
Blast demo commands
byte:blast.fasta.demo hqin$ cat commands.txt
blastp -subject db.faa -query query.faa
makeblastdb -in db2.faa
blastp -query my.seq.faa -db db2.faa | less
blastp -query my.seq.faa -db db2.faa -outfmt 6
blastp -query my.seq.faa -db db2.faa -outfmt 7 | less
#old version, still work on osX
blastall -p blastp -d db.faa -i query.faa -F F | less
bio386 20141008 1-100 lines in metric_v2.R
Went over metric_v2.R with two students.
I let students shares screen through GoogleHangout, and went line by line.
We finished 1-100 lines.
Problem. Students did not understand histogram.
I let students shares screen through GoogleHangout, and went line by line.
We finished 1-100 lines.
Problem. Students did not understand histogram.
Leek group genomics paper
https://github.com/jtleek/genomicspapers
Tuesday, October 7, 2014
Teaching professor conference
Call for Proposals: 2015 Teaching Professor Conference
The Call for Proposals for the 2015 Teaching Professor Conference is now open.
The Teaching Professor invites proposals for workshops and poster sessions for the 2015 Teaching Professor Conference, May 29-31 in Atlanta, Georgia.
Now in its 12th year, The Teaching Professor Conference provides a thought-provoking and stimulating forum for educators of all disciplines and experience levels to share practical ideas and best practices that advance college teaching and learning.
We invite submissions for the 45- and 75-minute concurrent sessions as well as poster sessions. Submissions should relate to one of the following topical areas, however compelling proposals that fall outside of these designated topics are welcome.
Featured topical areas are:
• Instructional Design
• Activities that Engage Students
• Teaching Specific Types of Students
• Instructional Vitality: Ways to Keep Teaching Fresh and Invigorated
• Teaching and Learning with Technology
• Creating Climates for Learning
• Faculty Development
Whether you are a new or returning presenter, we encourage you to seriously consider this opportunity to share your expertise at a conference of your peers. The deadline for submitting a proposal is October 31, 2014.
NOTE: Presenters are responsible for their own registration, hotel, and travel expenses. If you are unsure whether your institution would support your participation in the conference, please speak with your department chair before submitting a proposal.
Learn more about the submission process >> http://bit.ly/1pLtgEY
Mary Bart
Teaching Professor Group Manager
Editor, Faculty Focus
BIO233, ch8, gene regulation, lac operon, 20141007Tue, Brock 13th edition
10 minutes, Input results to googleDoc master sheet.
5 minutes, Go over exercises
Play-dough group exercise. (mark pens, pencils)
30 minutes, Playdough on major groove, toothpicks as basepairs. The major groove become obvious in the model.
1 hour: Lac operon. The class worked through 3 lac operon problems.
Questions can be designed for CAPbinding site or CAP or lacXYZ genes, such as frameshift. Frameshift in the one protein should not cause frame shit mutations in other genes in the same operon.
Mutation
Spring 2014 video recording:
https://www.youtube.com/watch?v=YzmGJgmrSQU
5 minutes, Go over exercises
Play-dough group exercise. (mark pens, pencils)
30 minutes, Playdough on major groove, toothpicks as basepairs. The major groove become obvious in the model.
1 hour: Lac operon. The class worked through 3 lac operon problems.
Questions can be designed for CAPbinding site or CAP or lacXYZ genes, such as frameshift. Frameshift in the one protein should not cause frame shit mutations in other genes in the same operon.
Mutation
https://www.youtube.com/watch?v=YzmGJgmrSQU
Monday, October 6, 2014
bio233 20131006 serial dilution, (LOH, regression ) lab, part 1
I spent about 45 minutes on pooling all cultures, do staggered dilutions, and measuring OD 600nm before class. Due to this rush, I to go over the material list before class (I forgot steril water, tally, trash can, marker pens, and the cultures.)
Some students are not sure to use which grids on hemocytometer.
Some students open the plate and let them stay on the bench.
The lab last from 2pm to 4:30pm.
I should leave the protocol online and ask student to answer some questions.
video:
http://youtu.be/4qlL4gvdCTQ
Some students are not sure to use which grids on hemocytometer.
Some students open the plate and let them stay on the bench.
The lab last from 2pm to 4:30pm.
I should leave the protocol online and ask student to answer some questions.
video:
http://youtu.be/4qlL4gvdCTQ
Thursday, October 2, 2014
Bio233 Chapter 7, Thu 20141002
1. Use playdough to build right and left hand alpha-helix.
2. Use playdough to do exercises on intron and exons, coding sequences. Where is the promoter sequece, AUG and stop codon? (Many student put AUG in front of exon1).
Interesting note: Students felt a bit disappointed when I told them to disemble their art work. I took pictures of their work with their name next to it. This seems to make them feel better.
Draw a concept map for central dogma (different between bacterial and eukaryotic species)
2. Use playdough to do exercises on intron and exons, coding sequences. Where is the promoter sequece, AUG and stop codon? (Many student put AUG in front of exon1).
Interesting note: Students felt a bit disappointed when I told them to disemble their art work. I took pictures of their work with their name next to it. This seems to make them feel better.
3. paper exercise on hairpin loops. (The grid that I provide for students are not large enough).
Classes ran out of time after 3 activities.
tRNA question and codon table
Draw a concept map for central dogma (different between bacterial and eukaryotic species)
Wednesday, October 1, 2014
Emerging research application
Abstract
http://www.emerging-
ERN Travel Awards
A limited number of student conference travel awards will be provided. Travel awards will cover transportation, hotel, and the conference registration fee. The conference registration fee is $400 per person. This fee covers the cost of meals provided during the conference.
Complete ERN travel award information is available on the conference website at http://www.emerging-
Key Dates Related to Abstract Submissions and Travel Awards
*** The deadline for abstract submissions is October 3, 2014.
*** Abstract acceptance and rejection notifications will be sent by November 11, 2014.
*** The deadline to submit travel award applications is October 3, 2014.
*** Travel awards will be announced by November 11, 2014.
For complete conference information, please visit the ERN Conference at website at http://www.emerging-
Using machine learning algorithm to identify genomic features that can predict longevity genes
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