Match the following descriptions to the most appropriate method of genome engineering presented within the list. Use each answer once. List: MuGENT, Transformation, CRISPR, Transposon mutagenesis, and MAGE.
a. You are attempting to see the effect of substituting similar amino acids across the genome (called conservative replacement). Thus, by using _____ you try and replace all glycine codons with alanines.
b. You are looking to create a heterogenous mixture of knockout mutants from a pool of 6 genes.
c. A broadly-applicable technique that can make efficient gene edits based on guide RNA.
d. You are looking to randomly disrupt genes within the genome to assess their function.
e. Using a PCR fragment with homology to the genome, you must get this DNA into your target cells somehow...
In: Biology
QUESTION 1
Which of the following is an enzyme?
|
a G protein |
||
|
a G protein-coupled receptor |
||
|
ATP |
||
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All of the above |
||
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None of the above |
1 points
QUESTION 2
Which of the following is true for all enzymes?
|
They alter the transition state. |
||
|
They decrease ΔG. |
||
|
They provide energy for endergonic reactions. |
||
|
They harness energy from ATP. |
1 points
QUESTION 3
The pathway of glycolysis can be found in:
|
Anaerobic bacteria only |
||
|
Anaerobic species only |
||
|
All bacteria, but not Eukaryotes |
||
|
All species |
1 points
QUESTION 4
Which of the following best explains why aerobic metabolism is "better" than anaerobic metabolism?
|
It produces water |
||
|
It produces CO2. |
||
|
It produces more ATP for every molecule of glucose oxidized. |
||
|
It doesn't require glucose. |
1 points
QUESTION 5
The Citric Acid Cycle nets _____ molecule(s) of ATP per molecule of glucose (assume GTP and ATP are interchangeable).
|
1 |
||
|
2 |
||
|
3 |
||
|
4 |
In: Biology
In: Biology
In: Biology
QUESTION 1
In a cross of AABB x aabb, how frequent are the individuals displaying the recessive trait for both genes in the F1 offspring?
|
0 |
||
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1/16 |
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3/16 |
||
|
9/16 |
||
|
100% |
QUESTION 2
If the amino acid sequence of the polypeptide chain below is written in the direction of its translation from the mRNA (from left to right), which amino acid has an exposed amino group?
Met Phe Leu Ser Tyr Cys Pro His Gln Arg Ile Thr
|
Met |
||
|
Thr |
||
|
Phe at the second position |
||
|
Both (a) and (b) |
||
|
None of the above. |
QUESTION 3
In order for a human (or another mammal) to grow to its normal size, the igf gene encoding the insulin-like growth factor
|
has to be imprinted in exactly the same way in both the sperm and the ovum. |
||
|
has to be imprinted in different ways (has to carry different epigenetic marks) in the sperm and in the ovum. |
||
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cannot be imprinted (cannot have any epigenetic mark whatsoever) in the gametes by either the male or the female parent. |
||
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has to be deleted in the sperm, but not in the ovum. |
||
|
None of the above. |
QUESTION 4
Lac operon transcription is _____________when the operator sequence is eliminated by a mutation
|
induced by the presence of glucose. |
||
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repressed |
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constitutive |
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not influenced at all |
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entirely blocked |
In: Biology
| SALARY | EDUC | EXPER | TIME |
| 39000 | 12 | 0 | 1 |
| 40200 | 10 | 44 | 7 |
| 42900 | 12 | 5 | 30 |
| 43800 | 8 | 6 | 7 |
| 43800 | 8 | 8 | 6 |
| 43800 | 12 | 0 | 7 |
| 43800 | 12 | 0 | 10 |
| 43800 | 12 | 5 | 6 |
| 44400 | 15 | 75 | 2 |
| 45000 | 8 | 52 | 3 |
| 45000 | 12 | 8 | 19 |
| 46200 | 12 | 52 | 3 |
| 48000 | 8 | 70 | 20 |
| 48000 | 12 | 6 | 23 |
| 48000 | 12 | 11 | 12 |
| 48000 | 12 | 11 | 17 |
| 48000 | 12 | 63 | 22 |
| 48000 | 12 | 144 | 24 |
| 48000 | 12 | 163 | 12 |
| 48000 | 12 | 228 | 26 |
| 48000 | 12 | 381 | 1 |
| 48000 | 16 | 214 | 15 |
| 49800 | 8 | 318 | 25 |
| 51000 | 8 | 96 | 33 |
| 51000 | 12 | 36 | 15 |
| 51000 | 12 | 59 | 14 |
| 51000 | 15 | 115 | 1 |
| 51000 | 15 | 165 | 4 |
| 51000 | 16 | 123 | 12 |
| 51600 | 12 | 18 | 12 |
| 52200 | 8 | 102 | 29 |
| 52200 | 12 | 127 | 29 |
| 52800 | 8 | 90 | 11 |
| 52800 | 8 | 190 | 1 |
| 52800 | 12 | 107 | 11 |
| 54000 | 8 | 173 | 34 |
| 54000 | 8 | 228 | 33 |
| 54000 | 12 | 26 | 11 |
| 54000 | 12 | 36 | 33 |
| 54000 | 12 | 38 | 22 |
| 54000 | 12 | 82 | 29 |
| 54000 | 12 | 169 | 27 |
| 54000 | 12 | 244 | 1 |
| 54000 | 15 | 24 | 13 |
| 54000 | 15 | 49 | 27 |
| 54000 | 15 | 51 | 21 |
| 54000 | 15 | 122 | 33 |
| 55200 | 12 | 97 | 17 |
| 55200 | 12 | 196 | 32 |
| 55800 | 12 | 133 | 30 |
| 56400 | 12 | 55 | 9 |
| 57000 | 12 | 90 | 23 |
| 57000 | 12 | 117 | 25 |
| 57000 | 15 | 51 | 17 |
| 57000 | 15 | 61 | 11 |
| 57000 | 15 | 241 | 34 |
| 60000 | 12 | 121 | 30 |
| 60000 | 15 | 79 | 13 |
| 61200 | 12 | 209 | 21 |
| 63000 | 12 | 87 | 33 |
| 63000 | 15 | 231 | 15 |
| 46200 | 12 | 12 | 22 |
| 50400 | 15 | 14 | 3 |
| 51000 | 12 | 180 | 15 |
| 51000 | 12 | 315 | 2 |
| 52200 | 12 | 29 | 14 |
| 54000 | 12 | 7 | 21 |
| 54000 | 12 | 38 | 11 |
| 54000 | 12 | 113 | 3 |
| 54000 | 15 | 18 | 8 |
| 54000 | 15 | 359 | 11 |
| 57000 | 15 | 36 | 5 |
| 60000 | 8 | 320 | 21 |
| 60000 | 12 | 24 | 2 |
| 60000 | 12 | 32 | 17 |
| 60000 | 12 | 49 | 8 |
| 60000 | 12 | 56 | 33 |
| 60000 | 12 | 252 | 11 |
| 60000 | 12 | 272 | 19 |
| 60000 | 15 | 25 | 13 |
| 60000 | 15 | 36 | 32 |
| 60000 | 15 | 56 | 12 |
| 60000 | 15 | 64 | 33 |
| 60000 | 15 | 108 | 16 |
| 60000 | 16 | 46 | 3 |
| 63000 | 15 | 72 | 17 |
| 66000 | 15 | 64 | 16 |
| 66000 | 15 | 84 | 33 |
| 66000 | 15 | 216 | 16 |
| 68400 | 15 | 42 | 7 |
| 69000 | 12 | 175 | 10 |
| 69000 | 15 | 132 | 24 |
| 81000 | 16 | 55 | 33 |
| SUMMARY OUTPUT | ||||||||
| Regression Statistics | ||||||||
| Multiple R | 0.549576953 | |||||||
| R Square | 0.302034828 | |||||||
| Adjusted R Square | 0.278507912 | |||||||
| Standard Error | 6027.28285 | |||||||
| Observations | 93 | |||||||
| ANOVA | ||||||||
| df | SS | MS | F | Significance F | ||||
| Regression | 3 | 1399124701 | 466374900.2 | 12.83784192 | 4.80E-07 | |||
| Residual | 89 | 3233204332 | 36328138.56 | |||||
| Total | 92 | 4632329032 | ||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
| Intercept | 31794.79804 | 3834.248408 | 8.29231564 | 1.09E-12 | 24176.22813 | 39413.36796 | 24176.22813 | 39413.368 |
| X Variable 1 | 1396.093359 | 277.1248641 | 5.037777335 | 2.45E-06 | 845.4521573 | 1946.734561 | 845.4521573 | 1946.73456 |
| X Variable 2 | 14.84048274 | 6.970537846 | 2.129029792 | 0.036013792 | 0.990172517 | 28.69079297 | 0.990172517 | 28.690793 |
| X Variable 3 | 206.290769 | 61.54401075 | 3.351922738 | 0.001179572 | 84.0041306 | 328.5774075 | 84.0041306 | 328.577407 |
3. Fit a multiple regression model that relates the salary to education, work experience, and time spent at the bank so far.
a - State what your model is.
b - Determine whether the independent variables are significant, or not, at a level of significance of 5%.
c - Which independent variable is most significant in explaining salary? Which is least significant?
d - Is your overall model significant? Provide statistical proof by conducting an F-test for overall fit of the regression. State the hypothesis to be tested, the p-value for your F-statistic, and your decision. How much weight of evidence is there in rejecting the null hypothesis?
In: Statistics and Probability
| SALARY | EDUC | EXPER | TIME |
| 39000 | 12 | 0 | 1 |
| 40200 | 10 | 44 | 7 |
| 42900 | 12 | 5 | 30 |
| 43800 | 8 | 6 | 7 |
| 43800 | 8 | 8 | 6 |
| 43800 | 12 | 0 | 7 |
| 43800 | 12 | 0 | 10 |
| 43800 | 12 | 5 | 6 |
| 44400 | 15 | 75 | 2 |
| 45000 | 8 | 52 | 3 |
| 45000 | 12 | 8 | 19 |
| 46200 | 12 | 52 | 3 |
| 48000 | 8 | 70 | 20 |
| 48000 | 12 | 6 | 23 |
| 48000 | 12 | 11 | 12 |
| 48000 | 12 | 11 | 17 |
| 48000 | 12 | 63 | 22 |
| 48000 | 12 | 144 | 24 |
| 48000 | 12 | 163 | 12 |
| 48000 | 12 | 228 | 26 |
| 48000 | 12 | 381 | 1 |
| 48000 | 16 | 214 | 15 |
| 49800 | 8 | 318 | 25 |
| 51000 | 8 | 96 | 33 |
| 51000 | 12 | 36 | 15 |
| 51000 | 12 | 59 | 14 |
| 51000 | 15 | 115 | 1 |
| 51000 | 15 | 165 | 4 |
| 51000 | 16 | 123 | 12 |
| 51600 | 12 | 18 | 12 |
| 52200 | 8 | 102 | 29 |
| 52200 | 12 | 127 | 29 |
| 52800 | 8 | 90 | 11 |
| 52800 | 8 | 190 | 1 |
| 52800 | 12 | 107 | 11 |
| 54000 | 8 | 173 | 34 |
| 54000 | 8 | 228 | 33 |
| 54000 | 12 | 26 | 11 |
| 54000 | 12 | 36 | 33 |
| 54000 | 12 | 38 | 22 |
| 54000 | 12 | 82 | 29 |
| 54000 | 12 | 169 | 27 |
| 54000 | 12 | 244 | 1 |
| 54000 | 15 | 24 | 13 |
| 54000 | 15 | 49 | 27 |
| 54000 | 15 | 51 | 21 |
| 54000 | 15 | 122 | 33 |
| 55200 | 12 | 97 | 17 |
| 55200 | 12 | 196 | 32 |
| 55800 | 12 | 133 | 30 |
| 56400 | 12 | 55 | 9 |
| 57000 | 12 | 90 | 23 |
| 57000 | 12 | 117 | 25 |
| 57000 | 15 | 51 | 17 |
| 57000 | 15 | 61 | 11 |
| 57000 | 15 | 241 | 34 |
| 60000 | 12 | 121 | 30 |
| 60000 | 15 | 79 | 13 |
| 61200 | 12 | 209 | 21 |
| 63000 | 12 | 87 | 33 |
| 63000 | 15 | 231 | 15 |
| 46200 | 12 | 12 | 22 |
| 50400 | 15 | 14 | 3 |
| 51000 | 12 | 180 | 15 |
| 51000 | 12 | 315 | 2 |
| 52200 | 12 | 29 | 14 |
| 54000 | 12 | 7 | 21 |
| 54000 | 12 | 38 | 11 |
| 54000 | 12 | 113 | 3 |
| 54000 | 15 | 18 | 8 |
| 54000 | 15 | 359 | 11 |
| 57000 | 15 | 36 | 5 |
| 60000 | 8 | 320 | 21 |
| 60000 | 12 | 24 | 2 |
| 60000 | 12 | 32 | 17 |
| 60000 | 12 | 49 | 8 |
| 60000 | 12 | 56 | 33 |
| 60000 | 12 | 252 | 11 |
| 60000 | 12 | 272 | 19 |
| 60000 | 15 | 25 | 13 |
| 60000 | 15 | 36 | 32 |
| 60000 | 15 | 56 | 12 |
| 60000 | 15 | 64 | 33 |
| 60000 | 15 | 108 | 16 |
| 60000 | 16 | 46 | 3 |
| 63000 | 15 | 72 | 17 |
| 66000 | 15 | 64 | 16 |
| 66000 | 15 | 84 | 33 |
| 66000 | 15 | 216 | 16 |
| 68400 | 15 | 42 | 7 |
| 69000 | 12 | 175 | 10 |
| 69000 | 15 | 132 | 24 |
| 81000 | 16 | 55 |
| SUMMARY OUTPUT | ||||||||
| Regression Statistics | ||||||||
| Multiple R | 0.41198516 | |||||||
| R Square | 0.16973178 | |||||||
| Adjusted R Square | 0.16060795 | |||||||
| Standard Error | 6501.12045 | |||||||
| Observations | 93 | |||||||
| ANOVA | ||||||||
| df | SS | MS | F | Significance F | ||||
| Regression | 1 | 786253429 | 786253429 | 18.60313 | 4.08E-05 | |||
| Residual | 91 | 3.85E+09 | 42264567.1 | |||||
| Total | 92 | 4.63E+09 | ||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
| Intercept | 38185.5979 | 3774.3766 | 10.117061 | 1.45E-16 | 30688.26252 | 45682.93 | 30688.26 | 45682.93 |
| X Variable 1 | 1280.85932 | 296.96712 | 4.31313512 | 4.08E-05 | 690.9706164 | 1870.748 | 690.9706 | 1870.748 |
This data set was obtained by collecting information on a randomly selected sample of 93 employees working at a bank.
SALARY- starting annual salary at the time of hire
EDUC - number of years of schooling at the time of the hire
EXPER - number of months of previous work experience at the time of hire
TIME - number of months that the employee has been working at the bank until now
2. Use the least squares method to fit a simple linear model that relates the salary (dependent variable) to education (independent variable).
a- What is your model? State the hypothesis that is to be tested, the decision rule, the test statistic, and your decision, using a level of significance of 5%.
b – What percentage of the variation in salary has been explained by the regression?
c – Provide a 95% confidence interval estimate for the true slope value.
d - Based on your model, what is the expected salary of a new hire with 12 years of education?
e – What is the 95% prediction interval for the salary of a new hire with 12 years of education? Use the fact that the distance value = 0.011286
In: Statistics and Probability
How many structures can you find to use as a starting dataset if you wanted to study how proteins interact with DNA. Assume that you will require only high resolution structures for the study (at least 2.5 Angstroms resolution). For the study, you plan to use structures that were only solved by X-ray crystallography. (Select the closest number if the exact number is not available) *
between 1000-1500
between 2700 - 4000
172
371
between 450 - 950
What is the UniProtKB? *
The UniProt Knowledgebase (UniProtKB) is the central hub for the collection of functional information on proteins, with accurate, consistent and rich annotation.
The UniProt Knowledgebase (UniProtKB) is the universal protein information center.
The UniProtKB is a database of unique protein sequences.
The UniProtKB is a database of conserved protein sequences.
The UniProtKB is a database of protein 3D structures using the Cartesian coordinate format.
Retrieve the database entry for the protein BPSL1549 from the GenBank database. What organism is the protein from? *
Burkholderia pseudomallei
Pseudomonas aeruginosa
Vibrio cholera
Burkholderia mallei
E. coli
Search the GenBank database for the database entry with the following accession number: MN908947. Select from the list below answers that are TRUE statements pertaining to that database entry. *
It is a nucleotide sequence composed of ~29,903 bp
The data is a genome sequence.
The data is the genome sequence of SARS-CoV-2
The data entry is from the order Nidovirales.
The data entry is from the order Coronavirales
The genome sequence was reported by Wuhan et al in the journalNature, 579, published in 2020.
The genome was isolated from patients who had suffered severe breathing difficulties that in some cases were fatal.
The organism caused a bacterial pneumonia that presented as a severe and acute respiratory symptoms.
The sequence was deposited into the GenBank database on 18 May 2020 and is the newest version of the COVID-19 sequence available.
In: Biology
Obtain expressions for dU, dH, dA, and dG for an ideal gas and for a van der Waals gas.
In: Chemistry
PLNIP is a gene found in the human genome that is responsible for the production of lipase. Lipase is a type of protein enzyme that digests lipids.
Some events in the creation of lipase
1. mRNA is brought to the ribosome
2. RNA polymerase copies PLNIP
3. elongation of polypeptide chain occurs
4. tRNA reads the codon UAA
The sequence in which the events numbered above occur when lipase is produced are ____, ____, ____, and ____.
(Record all four digits of your answer in the numerical response section of your answer key)
In: Biology