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Safe, fallen down this way, I want to be just what I am.Cocteau Twinssafe at lastmore quotes

words: exciting


EMBO Practical Course: Bioinformatics and Genome Analysis, 5–17 June 2017.


art + literature

daily quotation server archives

In the late 90’s I started (a good decade for starts) a daily quotation server project at www.quoteserver.ca. The domain is now defunct—some pages are partially viewable at the Way Back Machine.

Below is the list of quotes I had collected by the end of the life of the project. Most are about love—duh—and a few are jolly jests from funny trenches. You know, that place where mustard gas makes your eyes water.

The quotes weren’t scraped from quote archives—each is meaningful and hand-picked.

the quote archive

And now for full list of 1,600 other things worth reading. Such as everything Dorothy Parker has written and ... yes, even the Pinky and Brain quotes, which are a special kind of special.

Quote collections about love, heart, desire, life, death, god, mind, science.

Feeling lucky? Read 10 random quotes. Well, will you, punk?

Quotes about god

13
Take not God’s name in vain: select a time when it will have effect.
Ambrose Bierce
48
I love thee with the love I seemed to lose
With my lost saints,—I love thee with the breath
Smiles, tears, of all my life!—and, if God choose,
I shall but love thee better after death.
Elizabeth Barrett Browning
Sonnets from the Portuguese
104
Poems are made by fools like me,
But only God can make a tree.
Joyce Kilmer
Trees
117
All are but parts of one stupendous whole,
Whose body Nature is, and God the soul.
Alexander Pope
Essay on Man, Epistle i. 267.
243
Conceit is God’s gift to little men.
298
Poems are made by fools like me,
But only God can make a tree.
Joyce Kilmer
Trees
370
Men rarely (if ever) manage to dream up a god superior to themselves. Most gods have the manners and morals of a spoiled child.
Lazarus Long
Time Enough for Love
414
And, while with silent, lifting mind I’ve trod
The high untrespassed sanctity of space,
Put out my hand, and touched the face of God.
John Gillespie Magee, Jr.
452
God must love stupid people, He made so many of them.
457
If it turns out that there is a God, I don’t think that he’s evil. But the worst that you can say about him is that basically he’s an underachiever.
Woody Allen
556
% ar m God
ar: God does not exist
561
God made the integers; all else is the work of Man.
Kronecker
591
If you believe in the light, it’s because of obscurity.
If you believe in happiness it’s because of unhappiness.
If you believe in God, then you have to believe in the Devil.
Father X
Church of Notre Dame, Paris
609
O God, if there be a God, save my soul, if I have a soul!
611
See the happy moron,
He doesn’t give a damn.
I wish I were a moron.
My God! Perhaps I am!
706
An Apology for the Devil: It must be remembered that
we have only heard one side of the case. God has written
all the books.
Samuel Butler
Note Books
741
And almost every one when age,
Disease, or sorrows strike him,
Inclines to think there is a God,
Or something very like Him.
Arthur Hugh Clough
Dipsychus, sc. vi
783
So nigh is grandeur to our dust,
So near is God to man,
When Duty whispers low, Thou must,
The youth replies, I can.
Ralph Waldo Emerson
Voluntaries, iii
957
Gott ist tot: aber so wie die Art der Menschen ist,
wird es vielleicht noch jahrtausendlang Hohlen geben,
in denen man seinen Schatten zeigt.
[God is dead: but considering the state the species Man
is in, there will perhaps be caves, for ages yet, in which
his shadow will be shown.]
Friedrich Nietzsche
Ecce Homo
1082
O God! methinks it were a happy life,
To be no better than a homely swain;
To sit upon a hill, as I do now,
To carve out dials, quaintly, point by point,
Thereby to see the minutes how they run,
How many make the hour full complete;
How many hours bring about the day;
How many days will finish up the year;
How many years a mortal man may live.
William Shakespeare
Henry VII, Part III, II.v.21
1213
I loved you without hope, a mute offender;
What jealous pangs, what shy despairs I knew!
A love as deep as this, as true, as tender,
God grant another may yet offer you.
Alexander Pushkin
I Loved You Once
1218
I have heard the song of the blossoms and the old chant of the sea,
And seen strange lands from under the arched white sails of ships;
But the loveliest things of beauty God ever has showed to me,
Are her voice, and her hair, and eyes, and the dear red curve of her lips.
John Masefield
Beauty
1284
And this, O love, my pitiable plight
Whenever from my circling arms you stray;
This little world of mine has lost its light....
I hope to God, my dear, that you can say
The same to me.
Dorothy Parker
Rondeau Redouble
1333
How can I believe in God when just last week I got
my tongue caught in the roller of an electric typewriter?
Woody Allen
1334
Man is a god in ruins.
Ralph Waldo Emerson
1386
God made everything out of nothing, but the nothingness
shows through.
Paul Valery
1402
Which is it, is man one of God’s blunders or is
God one of man’s?
Friedrich Nietzsche
1416
Thank God men cannot as yet fly and lay waste the
sky as well as the earth!
Henry David Thoreau
1477
Nothing but blackness above
And nothing that moves but the cars...
God, if you wish for our love,
Fling us a handful of stars!
Louis Untermeyer
Caliban in the Coal Mines
1526
God is the immemorial refuge of the incompetent, the helpless, the miserable. They find not only sanctuary in His arms, but also a kind of superiority, soothing to their macerated egos; He will set them above their betters.
H.L. Mencken
1534
If the average man is made in God’s image, then a man such as Beethoven or Aristotle is plainly superior to God, and so God may be jealous of him, and eager to see his superiority perish with his bodily frame. All animal breeders know how difficult it is to maintain a fine strain. The universe seems to be in a conspiracy to encourage the endless reproduction of peasants and Socialists, but a subtle and mysterious opposition stands eternally against the reproduction of philosophers.
H.L. Mencken
In Defense of Women
1602
We turn toward God only to obtain the impossible.
Albert Camus
VIEW ALL

news + thoughts

Machine learning: a primer

Tue 05-12-2017
Machine learning extracts patterns from data without explicit instructions.

In this primer, we focus on essential ML principles— a modeling strategy to let the data speak for themselves, to the extent possible.

The benefits of ML arise from its use of a large number of tuning parameters or weights, which control the algorithm’s complexity and are estimated from the data using numerical optimization. Often ML algorithms are motivated by heuristics such as models of interacting neurons or natural evolution—even if the underlying mechanism of the biological system being studied is substantially different. The utility of ML algorithms is typically assessed empirically by how well extracted patterns generalize to new observations.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Machine learning: a primer. (read)

We present a data scenario in which we fit to a model with 5 predictors using polynomials and show what to expect from ML when noise and sample size vary. We also demonstrate the consequences of excluding an important predictor or including a spurious one.

Bzdok, D., Krzywinski, M. & Altman, N. (2017) Points of Significance: Machine learning: a primer. Nature Methods 14:1119–1120.",

...more about the Points of Significance column

Snowflake simulation

Tue 14-11-2017
Symmetric, beautiful and unique.

Just in time for the season, I've simulated a snow-pile of snowflakes based on the Gravner-Griffeath model.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
A few of the beautiful snowflakes generated by the Gravner-Griffeath model. (explore)

Gravner, J. & Griffeath, D. (2007) Modeling Snow Crystal Growth II: A mesoscopic lattice map with plausible dynamics.

Genes that make us sick

Thu 02-11-2017
Where disease hides in the genome.

My illustration of the location of genes in the human genome that are implicated in disease appears in The Objects that Power the Global Economy, a book by Quartz.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The location of genes implicated in disease in the human genome, shown here as a spiral. (more...)

Ensemble methods: Bagging and random forests

Mon 16-10-2017
Many heads are better than one.

We introduce two common ensemble methods: bagging and random forests. Both of these methods repeat a statistical analysis on a bootstrap sample to improve the accuracy of the predictor. Our column shows these methods as applied to Classification and Regression Trees.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Ensemble methods: Bagging and random forests. (read)

For example, we can sample the space of values more finely when using bagging with regression trees because each sample has potentially different boundaries at which the tree splits.

Random forests generate a large number of trees by not only generating bootstrap samples but also randomly choosing which predictor variables are considered at each split in the tree.

Krzywinski, M. & Altman, N. (2017) Points of Significance: Ensemble methods: bagging and random forests. Nature Methods 14:933–934.

Background reading

Krzywinski, M. & Altman, N. (2017) Points of Significance: Classification and regression trees. Nature Methods 14:757–758.

...more about the Points of Significance column

Classification and regression trees

Mon 16-10-2017
Decision trees are a powerful but simple prediction method.

Decision trees classify data by splitting it along the predictor axes into partitions with homogeneous values of the dependent variable. Unlike logistic or linear regression, CART does not develop a prediction equation. Instead, data are predicted by a series of binary decisions based on the boundaries of the splits. Decision trees are very effective and the resulting rules are readily interpreted.

Trees can be built using different metrics that measure how well the splits divide up the data classes: Gini index, entropy or misclassification error.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Classification and decision trees. (read)

When the predictor variable is quantitative and not categorical, regression trees are used. Here, the data are still split but now the predictor variable is estimated by the average within the split boundaries. Tree growth can be controlled using the complexity parameter, a measure of the relative improvement of each new split.

Individual trees can be very sensitive to minor changes in the data and even better prediction can be achieved by exploiting this variability. Using ensemble methods, we can grow multiple trees from the same data.

Krzywinski, M. & Altman, N. (2017) Points of Significance: Classification and regression trees. Nature Methods 14:757–758.

Background reading

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Logistic regression. Nature Methods 13:541-542.

Altman, N. & Krzywinski, M. (2015) Points of Significance: Multiple Linear Regression Nature Methods 12:1103-1104.

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Classifier evaluation. Nature Methods 13:603-604.

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Model Selection and Overfitting. Nature Methods 13:703-704.

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Regularization. Nature Methods 13:803-804.

...more about the Points of Significance column