allendalepharm Chapter 333 Writing Teaching Materials
Chapter 333 Writing Teaching Materials
[Course Name: Drug Comprehensive]
[Teacher: Tan Xi]
[Teaching classroom: Classroom 106, No. 1, Aerospace Town, Monday to Sunday from next week, 7 a.m. to 9 a.m.]
[Number of students: up to 350]
[Points standard: The points earned by the lecturer will be determined by the expert group after listening to the class. The student points standard is: 3000 points for passing, 5000 points for good, and 7000 points for excellence. Ending points will be awarded to a maximum of 350 students. No points will be awarded to students who are observing.]
Song He's face turns green, it's not that enemies don't get together!
I was actually teaching in the same classroom as Tan Xi!
The class times are still close together, Tan Xi’s class is in the first two periods in the morning, and his class is in the next two periods in the morning!
The gap in points is even greater. Students who signed up for Tanxi's courses scored a full 2,000 points higher in each grade at the end of the course!
"Snapped!"
Tan Xi took away his own paper and threw Song He's paper over.
"Did you see clearly? Do you know how big the difference is?" Tan Xi said with condescending contempt, "My class must be full, where is your class? I don't know if anyone will go!"
After saying that, Tan Xi strode away like a victor.
…
laboratory.
Song He sat at the table, holding his mobile phone and opening the Yuecheng Project APP.
As soon as it went online, a small red circle appeared in the background notification.
[Your course information has been uploaded and is temporarily unavailable for registration, but can be seen by all players]
[Please confirm that the course information is correct. After confirmation, registration will open at 18:00 tonight]
Song He opened the course and added a series of new courses. He scrolled down for a long time before finding his own course. He was overwhelmed by all the academic experts!
Check the information. If there is no problem, click Confirm.
I can only resign myself to fate. The points of the latest batch of courses are getting higher and higher, and my own class is ranked at the bottom. I hope that at least twenty or thirty students can sign up, so that the classroom will not be too deserted.
Don’t sign up with only three or five people, it will be too embarrassing once the class starts!
If there are only three or five people in a classroom that can accommodate 350 people, it will almost feel like the tutoring class is on the verge of bankruptcy. Moreover, there are too few students, and it is very likely that reliable laboratory assistants will not be selected, so what is the point of starting classes?
Song He sighed and opened his laptop.
Although there may not be many students, we still have to prepare teaching materials well and strive to teach one or two students clearly and bring them under our command.
Time is tight, so the textbook can’t contain any nonsense. It can only cover the whole article with practical information and list all the methods that may be used in the development of short sleeping pills!
I want to write a practical textbook... a practical textbook that can see the blood of a bayonet!
Song He put both hands on the keyboard and typed out the chapter content.
Chapter 1, Drug Mutual Prediction Method of Graph Neural Network SGCN Theory!
DDIs predict the side effects produced when two or more drugs are mixed, including the enhancement and weakening of drug efficacy, the enhancement and weakening of toxicity, and the emergence of other characteristics. Strengthening is considered a positive effect, weakening is considered a negative effect...
The forest prediction model combines multi-feature drugs and the dynamic routing mechanism of the capsule network to analyze drug effects, and combines the deep neural network DNN to predict each other...
Embedding DDIs prediction framework, encoding using node embeddings...
Chapter 2, Drug Prediction Method with Big Database!
By mapping the interaction affinity between small molecules of compounds and target genes, as well as the affinities of adjacent similar compounds, we can infer the possible efficacy and toxicity of unknown compounds...
For predicted compounds, experiments such as enzyme inhibitory activity and enzyme kinetics, radioligand competition, isothermal titration calorimetry, and nuclear magnetic resonance are used to test and determine...
When measuring the target gene data inhibition constant, Gibbs free energy, dissociation constant, and half inhibitory concentration, experimental mice and experimental monkeys can be used to conduct animal experiments...
Chapter 3, reference model drug prediction based on machine learning!
Chapter 4, Perceptually decoupled autoencoder extracts biological signals masked by confounding factors!
Chapter 5, AI-assisted prediction!
Chapter 6, Drug structure prediction using geometric deep learning!
Song He continued typing chapter by chapter, his hand speed was so fast that afterimages appeared, and the keyboard almost smoked.
The content of each chapter was learned when he was writing papers every day. Many of the contents were quite new and even came from papers a month or two ago. They were by no means comparable to ordinary lagging textbooks.
At the same time, in the process of writing the textbook, he also made a lot of changes of his own!
Any information that is obviously erroneous or questionable will be deleted. Occasionally, if there are some that are more typical, they will be placed in small print as discussion questions.
Song He even added a lot of his own original theories into it, which is considered an exclusive secret. After all, he has his own opinions on drugs after studying them for so long.
Before I knew it, a whole day passed.
Complete the last sentence of the textbook and click Save.
Look at the time, it's already 6:30 pm, and course registration has started half an hour ago!
Song He nervously picked up his phone and checked the number of applicants backstage.
He will decide how many copies of the textbook to print based on the number of applicants. If only three or five people signed up, printed dozens of copies and took them to the classroom, wouldn’t it look like a big injustice to the teacher?
The buffer circle rotated on the phone screen, showing the number of people who had reported.
Song He was stunned.
His face looked unbelievable!
"Is this...is there something wrong backstage?" Song He murmured to himself.