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This tutorial is best viewed in a Jupyter notebook! You can load this notebook one of the following ways

Launching the notebook in Jupyter in Galaxy

1. Instructions to Launch JupyterLab
2. Open a Terminal in JupyterLab with File -> New -> Terminal
3. Run wget https://training.galaxyproject.org/training-material/topics/data-science/tutorials/python-iterables/data-science-python-iterables.ipynb
4. Select the notebook that appears in the list of files on the left.

Downloading the notebook

1. Right click one of these links: Jupyter Notebook (With Solutions), Jupyter Notebook (Without Solutions)
2. Save Link As..

Agenda

In this tutorial, we will cover:

1. Lists
   1. Indexing
   2. Replacement
   3. Appending
   4. List Indices
   5. Removing Items.
   6. Empty Lists
   7. Heterogeneous Lists
   8. Strings are like Lists
   9. Bounds
   10. Exercises
2. Slicing & Dicing
   1. Stride
   2. Sorting
   3. Type Conversion
3. Exercise Time
   1. How Large is a Slice?
   2. Solution
   3. From Strings to Lists and Back
   4. Solution
   5. Working With the End
   6. Solution
   7. Stepping Through a List
   8. Solution
   9. Slice Bounds
   10. Solution
4. Dictionaries
   1. Methods
   2. Accessing Values
   3. Modifying Dictionaries
   4. Exercises
5. Maybe we’ve exterminated B.1.1.7 and B.1.351, remove their numbers.
6. Choosing the Right Data Type
   1. Exercises

Lists

Doing calculations with a hundred variables called pressure_001, pressure_002, etc. would be at least as slow as doing them by hand. Using a list to store many values together solves that problems. Lists are surrounded by square brackets: [, ], with values separated by commas:

pressures = [0.273, 0.275, 0.277, 0.275, 0.276]
print(f'pressures: {pressures}')
print(f'length: {len(pressures)}')

Indexing

You can use an item’s index to fetch it from a list.

print(f'zeroth item of pressures: {pressures[0]}')
print(f'fourth item of pressures: {pressures[4]}')

Replacement

Lists’ values can be changed or replaced by assigning a new value to the position in the list.

pressures[0] = 0.265
print(f'pressures is now: {pressures}')

Note how the first item has changed from 0.273

Appending

Appending items to a list lengthens it. You can do list_name.append() to add items to the end of a list.

primes = [2, 3, 5]
print(f'primes is initially: {primes}')
primes.append(7)
print(f'primes has become: {primes}')

.append() is a method of lists. It’s like a function, but tied to a particular object. You use object_name.method_name to call methods, which deliberately resembles the way we refer to things in a library.

We will meet other methods of lists as we go along. Use help(list) for a preview. extend is similar to append, but it allows you to combine two lists. For example:

teen_primes = [11, 13, 17, 19]
middle_aged_primes = [37, 41, 43, 47]
print(f'primes is currently: {primes}')
primes.extend(teen_primes)
print(f'primes has now become: {primes}')
primes.append(middle_aged_primes)
print(f'primes has finally become: {primes}')

Note that while extend maintains the “flat” structure of the list, appending a list to a list makes the result two-dimensional - the last element in primes is a list, not an integer.

This starts to become a more complicated data structure, and we’ll use more of these later. A list containing both integers and a list can be called a “hetereogenous” list, since it has multiple different data types. This is relatively uncommon, most of the lists you’ll encounter will have a single data type inside of them. Sometimes you’ll see a list of lists, which can be used to store positions, like a chessboard.

List Indices

In computer science and programming we number the positions within a list starting from 0, rather than from 1.

# Position  0         1          2            3           4
weekdays = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday']
print(weekdays[0])
print(weekdays[4])
print(weekdays[3])

But if you try an access a position that is outside of the list, you’ll get an error

print(weekdays[9])

returns a IndexError: list index out of range.

Tip: Reading Error Messages

So how do you read this?

1 | ---------------------------------------------------------------------------
2 | IndexError                                Traceback (most recent call last)
3 | /tmp/ipykernel_648319/137030145.py in <module>
4 | ----> 1 print(weekdays[9])
5 |
6 | IndexError: list index out of range

1. This is just a line of -s as a separator
2. IndexError, here Jupyter/CoCalc/etc are trying to be helpful and highlight the error for us. This is the important bit of information!
3. This is the path to where the code is, Jupyter/CoCalc/etc create temporary files to execute your code.
4. Here an arrow points to the line number where something has broken. 1 shows that it’s the first line within the cell, and it points to the print statement. Really it’s pointing at the weekdays[9] within the print statement.
5. Blank
6. This is where we normally look for the most important part of the Traceback. The error message. An IndexError, namely that the list index (9) is out of the range of possible values (the length of the list.)

However, sometimes you want to access the very end of a list! You can either start at the beginning and count along to find the last item or second to last item, or you can use Negative Indices

# Position  0         1          2            3           4
weekdays = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday']
# Position  -5        -4         -3           -2          -1

print(weekdays[-1])
print(weekdays[-2])
print(weekdays[-4])

If you wanted to find the last value in a list, you could also use len(elements) and then subtract back to find the index you want

elements[len(elements)-1]

This is essentially how negative indexes work, except you don’t have to use len(elements), that’s done for you automatically.

Removing Items.

You can use del to remove items from a list entirely. We use del list_name[index] to remove an element from a list (in the example, 9 is not a prime number) and thus shorten it. del is not a function or a method, but a statement in the language.

primes = [2, 3, 5, 7, 9]
print(f'primes before removing last item: {primes}')
del primes[4]
print(f'primes after removing last item: {primes}')

Empty Lists

The empty list contains no values. When you want to make a new list, use [] on its own to represent a list that doesn’t contain any values. This is helpful as a starting point for collecting values, which we’ll see soon.

Heterogeneous Lists

Lists may contain values of different types. A single list may contain numbers, strings, and anything else.

goals = [1, 'Create lists.', 2, 'Extract items from lists.', 3, 'Modify lists.']

Strings are like Lists

Text is often called a “string” in the programming world. Strings of text like name = "Helena" or patient_id = "19237zud830" are very similar conceptually to lists. Except instead of being a list of numbers, they’re a lists of characters.

In a number of older programming languages, strings are indeed arrays of numbers internally. However python hides a lot of that complexity from us, so we can just work with text.

Still, many of the operations you use on lists, can also be used on strings as well! Strings can be indexed like lists so you can get single elements from lists.

element = 'carbon'
print(f'zeroth character: {element[0]}')
print(f'third character: {element[3]}')

Strings, however, cannot be modified, you can’t change a single letter in a string. Things that cannot be modified after creation are called immutable or sometimes frozen, compared to things which can be modified which are called mutable. Python considers the string to be a single value with parts, not a collection of values.

element[0] = 'C'

Bounds

You cannot access values beyond the end of the list, this will result in an error. Python reports an IndexError if we attempt to access a value that doesn’t exist. This is a kind of runtime error, as it cannot be detected as the code is parsed. Imagine if you had a script which let you read in a file, depending on how many lines were in the file, whether index 90 was valid or invalid, would depend on how big your file was.

print(f'99th element of element is: {element[99]}')

Exercises

Question: Checking suffixes

1. How could you check that the extension of a filename is .csv
2. Can you find another way? Maybe check the help page for str

Solution

1. a[-4:] == "csv" (Here we use == for comparing two values)
2. a.endswith('.csv')

# Test code here!
a = "1234.csv"
b = "1273.tsv"
c = "9382.csv"
d = "1239.csv"

Question: Say it loud!

1. Can you find a method in the str’s help that converts the string to upper case
2. or lower case?
3. Can you use it to fix mixed case DNA sequence?

Solution

1. "shout it out".upper()
2. "WHISPER THIS".lower()
3. terrible_sequence.upper()

# Test answers here!
print("shout it out")
print("WHISPER THIS")
# Fix this mess to be all capital
terrible_sequence = "AcTGAGccGGTt"
print(terrible_sequence)

Question: Splitting

1. We use .split() to split a string by some character. Here we have a comma separated list of values, try splitting that up by a comma, but we actually wanted it separated by | characters. Can you split it up, and then re-join it with that new character?
2. Does help(str) give you another option for replacing a character like that.
3. What happens if you split by another value like 3?

Solution

1. data.split(",")
2. data.replace(",", "|")
3. Those characters will disappear! If you want to reconstruct the same string

# Split me
data = "0,0,1,3,1,2,4,7,8,3,3,3,10,5,7,4,7,7,12,18,6,13,11,11,7,7,4,6,8,8,4,4,5,7,3,4,2,3,0,0"

Slicing & Dicing

All of the data types we’ve talked about today can be sliced, and this will be a key part of using lists.

elements = ['H', 'He', 'Li', 'Be', 'B', 'C', 'N', 'O', 'F']
# Instead of accessing a single element
print(elements[0])
# We'll access a range
print(elements[0:4])

Accessing only a portion of a list is commonly used, say if you have a list of FastQ files from paired end sequencing, perhaps you want two of them at a time. You could access those with [0:2].

# You don't need to start at 0
print(elements[6:8])

# But your end should be bigger than your start.
# What do you think this will return?
# Make a guess before you run it
print(elements[6:5])

If you don’t supply an end value, Python will default to going to the end of the list. Likewise, if you don’t provide a start value, Python will use 0 as the start by default, until whatever end value you provide.

Question: Valid and Invalid Slices

Which of these do you think will be valid? Which are invalid? Predict what they will return:

# 1
elements = ['H', 'He', 'Li', 'Be', 'B', 'C', 'N', 'O', 'F']
# 2
elements[0:3]
# 3
elements[:3]
# 4
elements[-3:3]
# 5
elements[-8:-3]
# 6
elements[:]
# 7
elements[0:20]
# 8
elements['H':'Li']
# 9
elements[1.5:]

Solution

All of these are valid except the last two.

1. If you dont’ fill in a position, Python will use the default. 0 for the left hand side of the :, and len(elements) for the right hand side.
2. You can request a slice longer than your list (e.g. up to 20), but Python may not give you that many items back.
3. List slicing can only be done with integers, not floats.

# Check your answers here!

Stride

However, list slicing can be more complicated. You can additionally use a ‘stride’ parameter, which is how Python should strep through the list. To take every other element from a list:

values = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
print(values[0:12:2]) # every other value
print(values[1:12:2]) # every other value from the second value
print(values[::2]) # the start and end are optional
print(values[::3]) # every third value in the list.

So list slicing together is either list[low:high] or list[low:high:stride], where low and high are optional if you just want to go to the end of the list.

Sorting

Lists occasionally need to be sorted. For example, you have a list of students you might want to alphabetise, and here you can use the function sorted to help you.

students = [
    'Koos Christabella',
    'Zackary Habiba',
    'Jumana Rostam',
    'Sorina Gaia',
    'Kalyani Bessarion',
    'Enéas Nirmala',
    '王奕辰',
    '刘依诺',
]
students = sorted(students)
print(students)

Tip: Sorting names is hard!

Some people have 1 name, some have 4 or more! Some cultures have surnames first, some not. Sorting names is a complex situation, so be sure you consider your data before sorting and assuming it’s correct. Test with multiple values to make sure your code works!

Tip: Results can be dependent on analysis order!

Some analyses (especially simultaions) can be dependent on data input order or data sorting. This was recently seen in Neupane et al. 2019 where the data files used were sorted one way on Windows, and another on Linux, resulting in different results for the same code and the same datasets! Yikes!

If you know your analyses are dependent on file ordering, then you can use sorted() to make sure the data is provided in a uniform way every time.

If you’re not sure if your results will be dependent, you can try sorting anyway. Or better yet, randomising the list of inputs to make sure your code behaves properly in any scenario.

Type Conversion

Just list with converting "1.5" to an float with the float() function, or 3.1 to a string with str(), we can do the same with lists using the list() function, and sets with set():

# Convert text to a list
print(list("sometext"))

Converting a list back into text is likewise possible, but you need to use the special function join. Join is a function of a str, which accepts a list

word = ['c', 'a', 'f', 'e']
print("-".join(word))

It takes the string you called it on, and uses that as a separator. Then for the list that you provide, it joins that together with the separator.

Exercise Time

Question: Fill in the Blanks

Fill in the blanks so that the program below produces the output shown.

values = ____
values.____(1)
values.____(3)
values.____(5)
print(f'first time: {values}')
values = values[____]
print(f'second time: {values}')

first time: [1, 3, 5]
second time: [3, 5]

Solution

values = []
values.append(1)
values.append(3)
values.append(5)
print(f'first time: {values}')
values = values[1:]
print(f'second time: {values}')

# Fill in the blanks here!

values = ____
values.____(1)
values.____(3)
values.____(5)
print(f'first time: {values}') # Should print [1, 3, 5]
values = values[____]
print(f'second time: {values}') # should print [3, 5]

How Large is a Slice?

If start and stop are both non-negative integers, how long is the list values[start:stop]?

Solution

The list values[start:stop] has up to stop - start elements. For example, values[1:4] has the 3 elements values[1], values[2], and values[3]. Why ‘up to’? If stop is greater than the total length of the list values, we will still get a list back but it will be shorter than expected.

From Strings to Lists and Back

Given this:

print(f'string to list: {list('tin')}')
print(f'list to string: {''.join(['g', 'o', 'l', 'd'])}')

1. What does list('some string') do?
2. What does '-'.join(['x', 'y', 'z']) generate?

Solution

1. list('some string') converts a string into a list containing all of its characters.
2. join returns a string that is the concatenation of each string element in the list and adds the separator between each element in the list. This results in x-y-z. The separator between the elements is the string that provides this method.

# Test code here

Working With the End

What does the following program print?

element = 'helium'
print(element[-1])

1. How does Python interpret a negative index?
2. If a list or string has N elements, what is the most negative index that can safely be used with it, and what location does that index represent?
3. If values is a list, what does del values[-1] do?
4. How can you display all elements but the last one without changing values? (Hint: you will need to combine slicing and negative indexing.)

Solution

The program prints m.

1. Python interprets a negative index as starting from the end (as opposed to starting from the beginning). The last element is -1.
2. The last index that can safely be used with a list of N elements is element -N, which represents the first element.
3. del values[-1] removes the last element from the list.
4. values[:-1]

# Test code here

Stepping Through a List

What does the following program print?

element = 'fluorine'
print(element[::2])
print(element[::-1])

1. If we write a slice as low:high:stride, what does stride do?
2. What expression would select all of the even-numbered items from a collection?

Solution

The program prints

furn
eniroulf

1. stride is the step size of the slice.
2. The slice 1::2 selects all even-numbered items from a collection: it starts with element 1 (which is the second element, since indexing starts at 0), goes on until the end (since no end is given), and uses a step size of 2 (i.e., selects every second element).

# Test code here

Slice Bounds

What does the following program print?

element = 'lithium'
print(element[0:20])
print(element[-1:3])

Solution

lithium

The first statement prints the whole string, since the slice goes beyond the total length of the string. The second statement returns an empty string, because the slice goes “out of bounds” of the string.

# Test code here

Dictionaries

When you think of a Dictionary, you should think of a real life Dictionary, they map some key to a value. Like a term to it’s definition

Or a Country to it’s population

In Python we create a dictionary with {} and use : to separate keys and values. Turning the above list into a Python dictionary, it would look like:

populations = {
  "South Sudan": 492970,
  "Australia": 411667,
  "Guinea": 1660973,
  "Morocco": 573895,
  "Maldives": 221678,
  "Wallis and Futuna": 1126,
  "Eswatini": 94874,
  "Namibia": 325858,
  "Turkmenistan": 1031992,
}

You can see a string (the country name) being used for the key, and then the number (an integer) as the value. (Would a float make sense? Why or why not?)

Tip: Other Names

They’re also sometimes called associative arrays (because they’re an array or list of values that associate a key to a value) or maps (because they map a key to a value), depending on what you’re reading.

Methods

You can access both the keys, and the values

print(populations.keys())
print(populations.values())

These will print out two list-like objects. They will become more useful in the future when we talk about looping over dictionaries and processing all of the values within.

Accessing Values

Just like lists where you access by the position in the list

print(populations["Namibia"])

And just like lists, if you try an access a key that isn’t there or an index outside of the range of the list:

print(populations["Mars"])

Tip: Dictionaries are faster than lists for looking up values

Just like in real life, searching a dictionary for a specific term is quite fast. Often a lot faster than searching a list for a specific value.

For those of you old enough to remember the paper version of a dictionary, you knew that As would be at the start and Zs at the end, and probably Ms around the middle. And if you were looking for a word like “Squirrel”, you’d open the dictionary in the middle, maybe decide it was in the second half of the book, randomly choose a page in the second half, and you could keep deciding if it was “before” or “after” the current page, never even bothering to search the first half.

Conceptually, compared with a list, you can’t make this guess of if the item is in the first or second half. You need to search item by item, it would be like reading page by page until you get to Squirrel in the dictionary.

Modifying Dictionaries

Adding new values to a dictionary is easy, it’s very similar to replacing a value in a list.

# For lists we did
x = ['x', 'y', 'z']
x[0] = 'a'
print(x)

For dictionaries, it’s essentially the same, we access the ‘place’ in the dictionary just like we did with a list, and set it to a value

populations["Mars"] = 6 # robots
print(populations)

And similarly, removing items is the same as it was for lists:

print(x)
del x[0] # Removes the first item
print(x)

And with dictionaries you delete by specifying which position/key you want to remove

del populations['Australia']
print(populations)

Exercises

Question: DNA Complement

DNA is usually in the form of dsDNA, a paired strand, where A maps to T and C maps to G and vice versa. But when we’re working with DNA sequences in bioinformatics, we often only store one strand, because we can calculate the complement on the fly, when we need.

Write a dictionary that lets you look up the letters A, C, T, and G and find their complements.

Solution

You need to have the complements of every base. If you just defined ‘A’ and ‘C’, how would you look up the complement when you want to translate a ‘T’ or a ‘G’? It’s not easily possible to look up a key by a value, only to search a key and find a value.

translation = {
'A': 'T',
'T': 'A',
'C': 'G',
'G': 'C',
}

# Test code here!
translation = {

}
print(translation)

Question: Modifying an array

Fill in the blanks to make the execution correct:

variants = {
  'B.1.1.7': 26267,
  'B.1.351': 439,
}
variants[_____] =  _____
print(variants) # Should print {'B.1.1.7': 26267, 'B.1.351': 439, 'P.1': 384}
__________
print(variants) # Should print {'B.1.1.7': 26267, 'B.1.351': 439, 'P.1': 384, 'B.1.617.2': 43486}
# Maybe we've exterminated B.1.1.7 and B.1.351, remove their numbers.
del _______
del _______
print(variants[______]) # Should print 384
print(variants[______]) # Should print 43486

Solution

variants = { ‘B.1.1.7’: 26267, ‘B.1.351’: 439, } variants[‘P.1’] = 384 print(variants) # Should print {‘B.1.1.7’: 26267, ‘B.1.351’: 439, ‘P.1’: 384} variants[‘B.1.617.2’] = 43486 print(variants) # Should print {‘B.1.1.7’: 26267, ‘B.1.351’: 439, ‘P.1’: 384, ‘B.1.617.2’: 43486}

Maybe we’ve exterminated B.1.1.7 and B.1.351, remove their numbers.

del variants[‘B.1.1.7’] del variants[‘B.1.351’] print(variants[‘P.1’]) # Should print 384 print(variants[‘B.1.617.2’]) # Should print 43486 ```

# Test code here!
variants = {
  'B.1.1.7': 26267,
  'B.1.351': 439,
}
variants[_____] =  _____
print(variants) # Should print {'B.1.1.7': 26267, 'B.1.351': 439, 'P.1': 384}
__________
print(variants) # Should print {'B.1.1.7': 26267, 'B.1.351': 439, 'P.1': 384, 'B.1.617.2': 43486}
# Maybe we've exterminated B.1.1.7 and B.1.351, remove their numbers.
del _______
del _______
print(variants[______]) # Should print 384
print(variants[______]) # Should print 43486

Choosing the Right Data Type

Choosing the correct data type can sometimes require some thought, and even discussion with colleagues. And don’t be afraid to search the internet for how other people have done it!

Exercises

Question: Which Datatype

1. Chromosome Length
2. Name
3. Weight
4. Sex
5. Hair Colour
6. Money/Currency

Solution

1. Here you need to use an integer, a fractional or float value would not make sense. You cannot have half an A/C/T/G.
2. Here a string would be a good choice. (And probably just a single name string, rather than a first and last name, as not all humans have two names! And some have more than two.)
3. An integer is good type for storing weight, if you are using a small unit (e.g. grams). Otherwise you might consider a float, but you’d need to be careful to format it properly (e.g. {value:0.2f}) when printing it out. It depends on the application.
4. This is a case where you should consider carefully the application, but bool is usally the wrong answer. Are you recording patient data? Is their expressed gender the correct variable or did you need sex? Miyagi et al. 2021 goes into detail on this multifaceted issue in a medical research context. For example chromosomal sex is also more complicated and cannot be stored with a true/false value, as people with Kleinfelters exist. A string can be an ok choice here.
5. There is a limited vocabulary humans use to describe hair colour, so a string can be used, or a data type we haven’t discussed! An enum is an enumeration, and when you have a limited set of values that are possible, you can use a enum to double check that whatever value is being used (or read from a file, or entered by a user) matches one of the “approved” values.
6. A float is a good guess, but with floats come weird rounding issues. Often times people choose to use an integer storing the value in cents (or fractional cents, to whatever the desired precision is).

Key points

• A list stores many values in a single structure.

• Use an item’s index to fetch it from a list.

• Lists’ values can be replaced by assigning to them.

• Appending items to a list lengthens it.

• Use del to remove items from a list entirely.

• The empty list contains no values.

• Lists may contain values of different types.

• Character strings can be indexed like lists.

• Character strings are immutable.

• Indexing beyond the end of the collection is an error.

Frequently Asked Questions

References

1. Neupane, J. B., R. P. Neupane, Y. Luo, W. Y. Yoshida, R. Sun et al., 2019 Characterization of Leptazolines A–D, Polar Oxazolines from the Cyanobacterium Leptolyngbya sp., Reveals a Glitch with the “Willoughby–Hoye” Scripts for Calculating NMR Chemical Shifts. Organic Letters 21: 8449–8453. 10.1021/acs.orglett.9b03216
2. Miyagi, M., E. M. Guthman, and S. D.-K. Sun, 2021 Transgender rights rely on inclusive language. Science 374: 1568–1569. 10.1126/science.abn3759

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Citing this Tutorial

1. The Carpentries, Helena Rasche, Donny Vrins, Bazante Sanders, 2022 Python - Lists & Strings & Dictionaries (Galaxy Training Materials). https://training.galaxyproject.org/training-material/topics/data-science/tutorials/python-iterables/tutorial.html Online; accessed TODAY
2. Batut et al., 2018 Community-Driven Data Analysis Training for Biology Cell Systems 10.1016/j.cels.2018.05.012

BibTeX

@misc{data-science-python-iterables,
author = "The Carpentries and Helena Rasche and Donny Vrins and Bazante Sanders",
title = "Python - Lists & Strings & Dictionaries (Galaxy Training Materials)",
year = "2022",
month = "09",
day = "28"
url = "\url{https://training.galaxyproject.org/training-material/topics/data-science/tutorials/python-iterables/tutorial.html}",
note = "[Online; accessed TODAY]"
}
@article{Batut_2018,
    doi = {10.1016/j.cels.2018.05.012},
    url = {https://doi.org/10.1016%2Fj.cels.2018.05.012},
    year = 2018,
    month = {jun},
    publisher = {Elsevier {BV}},
    volume = {6},
    number = {6},
    pages = {752--758.e1},
    author = {B{\'{e}}r{\'{e}}nice Batut and Saskia Hiltemann and Andrea Bagnacani and Dannon Baker and Vivek Bhardwaj and Clemens Blank and Anthony Bretaudeau and Loraine Brillet-Gu{\'{e}}guen and Martin {\v{C}}ech and John Chilton and Dave Clements and Olivia Doppelt-Azeroual and Anika Erxleben and Mallory Ann Freeberg and Simon Gladman and Youri Hoogstrate and Hans-Rudolf Hotz and Torsten Houwaart and Pratik Jagtap and Delphine Larivi{\`{e}}re and Gildas Le Corguill{\'{e}} and Thomas Manke and Fabien Mareuil and Fidel Ram{\'{\i}}rez and Devon Ryan and Florian Christoph Sigloch and Nicola Soranzo and Joachim Wolff and Pavankumar Videm and Markus Wolfien and Aisanjiang Wubuli and Dilmurat Yusuf and James Taylor and Rolf Backofen and Anton Nekrutenko and Björn Grüning},
    title = {Community-Driven Data Analysis Training for Biology},
    journal = {Cell Systems}
}
                   

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