kenthorvath

/* Solarized Dark 

For use with Jekyll and Pygments

http://ethanschoonover.com/solarized

SOLARIZED HEX      ROLE
--------- -------- ------------------------------------------
base03    #002b36  background
base01    #586e75  comments / secondary content

kenthorvath

<?xml version="1.0"?>
<root>
	<item>
		<name>F19 to F19</name>
		<appendix>(F19 to Hyper (ctrl+shift+cmd+opt) + F19 Only, send escape)</appendix>
		<identifier>private.f192f19_escape</identifier>
		<autogen>
			--KeyOverlaidModifier--
			KeyCode::F19,
			KeyCode::COMMAND_L,

kenthorvath

#Kent's Thesis Defense ##Questions and Answers to Consider

###[Q1] - Is there any evidence for SLX4 involvement in ALT cancers? Or more specifically, do Fanconi patients have any increased/decreased incidence of ALT-cancers?

Our findings indicate that ALT-type cancers have an abundance of SLX4 localization to telomeres. Other members of our lab have found SLX4 knockdown results in substantial impairment of ALT-cell proliferation and colony survival. As ALT-type cancers typically have extremely long telomeres, we believe SLX4 may be involved in telomere maintenance in these cells. Thus, Fanconi patients with defects in SLX4/FANCP may be less likely to develop ALT-type cancers. However, the first FANCP patients have only been recently identified, and there is not much literature regarding the telomeric maintenance pathways in FANCP-related cancers.

###[Q2] - What kinds of cancers do SLX4 knockout mice develop? Is there any information about the telomeric maintenance pathways in these mice?

###[Q3] - Do SLX4

kenthorvath

How many unique permutations are there for a sequence of size n with n_i number of elements of type e_i?

E.g. 

The sequence [a a b b] has 4 elements with n_1 = 2; n_2 = 2; and elements e_1 = a and e_2 = b.

The unique permutations of this sequence are:

1: a a b b
2: a b a b

kenthorvath

#--------------------------------------------------------------------------
# Nathan's thief of Baghdad problem.
#
#   Expected time to reach exit = 4.03 +/- 0.02 days ; based on 1e5 trials
#--------------------------------------------------------------------------

import numpy as np
from scipy.stats.mstats import sem

def solve(time_sum):