请双击下面的英文字幕来播放视频。
翻译人员: Zehan Ma
校对人员: Bangyou Xiang
00:12
I am a translator.
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我是一名翻译。
00:14
I translate from biology into mathematics
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我把生物学翻译成数学,
00:17
and vice versa.
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反之亦然。
00:19
I write mathematical models
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我建造数学模型,
00:21
which, in my case, are systems
of differential equations,
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用微分方程组,
00:24
to describe biological mechanisms,
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来描述生物学机制,
00:26
such as cell growth.
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比如说细胞的生长。
00:28
Essentially, it works like this.
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基本来说,运作过程如下。
00:30
First, I identify the key elements
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首先,我找出关键的元素,
00:33
that I believe may be driving
behavior over time
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那些我认为
可能会随着时间的推移,
00:35
of a particular mechanism.
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影响某些特定机制运作的元素。
00:38
Then, I formulate assumptions
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然后,我做出假设,
00:40
about how these elements
interact with each other
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猜测这些元素
如何与彼此互动,
00:43
and with their environment.
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与它们的环境互动。
00:44
It may look something like this.
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可能看起来像这样。
00:46
Then, I translate
these assumptions into equations,
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然后,我把这些假设
翻译成方程,
00:50
which may look something like this.
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它看起来可能像这样。
00:53
Finally, I analyze my equations
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最后,我分析我的方程,
00:55
and translate the results back
into the language of biology.
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并把结果翻译回生物学语言。
01:00
A key aspect of mathematical modeling
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数学建模的一个关键点在于,
01:02
is that we, as modelers,
do not think about what things are;
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我们作为建模者,
不是想这些东西“是”什么,
01:06
we think about what they do.
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而是想它们“做”什么。
01:08
We think about relationships
between individuals,
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我们思考个体之间的关系,
01:10
whether they be cells, animals or people,
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不管这些个体是细胞、动物还是人,
01:13
and how they interact with each other
and with their environment.
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我们想它们如何与彼此相互影响、
与它们周围的环境相互影响。
01:17
Let me give you an example.
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让我来举个例子。
01:19
What do foxes and immune cells
have in common?
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狐狸和免疫细胞之间
有什么共同点?
01:24
They're both predators,
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它们都是捕食者,
01:26
except foxes feed on rabbits,
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只不过狐狸吃兔子,
01:29
and immune cells feed on invaders,
such as cancer cells.
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而免疫细胞以入侵者为食,
比如说癌细胞。
01:33
But from a mathematical point of view,
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但是从数学的角度来说,
01:35
a qualitatively same system
of predator-prey type equations
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用本质上相同的
捕食者——猎物方程系统,
01:39
will describe interactions
between foxes and rabbits
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就能描述狐狸与兔子
之间的相互影响
01:43
and cancer and immune cells.
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还有癌细胞与免疫细胞
之间的相互影响。
01:45
Predator-prey type systems
have been studied extensively
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捕食者——猎物类型的方程系统,
01:48
in scientific literature,
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已经在科学文献中被广泛研究,
01:49
describing interactions
of two populations,
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它被用来描述
两个种群之间的相互影响,
01:52
where survival of one depends
on consuming the other.
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其中一个种群吃掉另一个种群
才能得以生存。
01:55
And these same equations
provide a framework
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也就是这些方程为我们
提供了一个框架
01:58
for understanding
cancer-immune interactions,
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来了解癌细胞与免疫系统
之间的相互影响,
02:00
where cancer is the prey,
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在这套方程中,癌细胞是猎物,
02:02
and the immune system is the predator.
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免疫系统是捕食者。
02:04
And the prey employs all sorts of tricks
to prevent the predator from killing it,
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猎物会采用一切诡计
来防止被捕食者杀死,
02:08
ranging from camouflaging itself
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从伪装自己,
02:10
to stealing the predator's food.
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到偷走捕食者的食物。
02:13
This can have some very
interesting implications.
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这可能会产生一些非常有趣的情况。
02:15
For example, despite enormous successes
in the field of immunotherapy,
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举例来说,尽管我们在免疫疗法领域
取得了巨大的成就,
02:20
there still remains
somewhat limited efficacy
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但在面对实体恶性肿瘤时,
02:23
when it comes solid tumors.
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其疗效还是十分有限的。
02:25
But if you think about it ecologically,
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但如果从生态学的观点来思考的话,
02:28
both cancer and immune cells --
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不管是癌细胞和免疫细胞——
02:30
the prey and the predator --
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即猎物和捕食者——
02:31
require nutrients
such as glucose to survive.
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都需要营养(如葡萄糖)来生存。
02:35
If cancer cells outcompete
the immune cells for shared nutrients
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如果癌细胞比免疫细胞
摄入的共享养分更多,
02:40
in the tumor microenvironment,
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在肿瘤的微环境中,
02:41
then the immune cells will physically
not be able to do their job.
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免疫细胞就不能够
完成它们的工作。
02:46
This predator-prey-shared
resource type model
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这种
捕食者—猎物—共享资源类的模型,
02:49
is something I've worked on
in my own research.
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是我一直在研究的。
02:51
And it was recently shown experimentally
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最近的实验表明
02:54
that restoring the metabolic balance
in the tumor microenvironment --
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恢复肿瘤微环境中的
新陈代谢平衡——
02:58
that is, making sure
immune cells get their food --
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也就是确保免疫细胞
得到它们的食物——
03:01
can give them, the predators, back
their edge in fighting cancer, the prey.
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可以使免疫细胞(捕食者)在
与癌细胞(猎物)对抗时找回优势。
03:08
This means that if you abstract a bit,
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意思就是,抽象一点来想,
03:10
you can think about cancer itself
as an ecosystem,
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你可以把癌细胞自身
想象成一个生态系统,
03:13
where heterogeneous populations of cells
compete and cooperate
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在这个系统中,多样的细胞种群
相互竞争、相互合作
03:18
for space and nutrients,
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来获取空间和营养,
03:20
interact with predators --
the immune system --
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与捕食者——免疫细胞相互影响,
03:22
migrate -- metastases --
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迁移,也就是新陈代谢……
03:25
all within the ecosystem
of the human body.
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这全都发生在人体
这个生态系统之中。
03:28
And what do we know about most
ecosystems from conservation biology?
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那么,从生物保护的角度来看,
我 们对大多数生态系统有哪些了解?
03:32
That one of the best ways
to extinguish species
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那就是,让一个物种灭绝的
最佳方式之一,
03:35
is not to target them directly
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不是直接毁灭物种本身,
03:37
but to target their environment.
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而是破坏它们所生存的环境。
03:40
And so, once we have identified
the key components
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这样一来,一旦我们明确了
03:43
of the tumor environment,
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肿瘤环境的关键成分,
03:45
we can propose hypotheses
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我们可以做出假设,
03:47
and simulate scenarios
and therapeutic interventions
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模拟情景,然后进行干预治疗,
03:50
all in a completely safe
and affordable way
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这全部采用一种十分安全
和实惠的方法
03:54
and target different components
of the microenvironment
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之后以微环境中不同的成分为目标
03:57
in such a way as to kill the cancer
without harming the host,
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在不危害宿主的情况下
杀死癌细胞,
04:01
such as me or you.
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宿主可以是你,或者是我。
04:05
And so while the immediate
goal of my research
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所以,当前我研究的直接目标,
04:08
is to advance research and innovation
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是推动研究与创新的发展
04:10
and to reduce its cost,
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降低成本,
04:12
the real intent, of course,
is to save lives.
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当然,真实的目的是拯救生命。
04:15
And that's what I try to do
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这也是我一直在尝试的,
04:17
through mathematical modeling
applied to biology,
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将数学建模应用于生物学,
04:19
and in particular,
to the development of drugs.
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特别是应用于药物的开发上。
04:22
It's a field that until relatively
recently has remained somewhat marginal,
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直到最近,
这都还是一个有些边缘化的领域,
04:26
but it has matured.
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但它已经成熟。
04:28
And there are now very well-developed
mathematical methods,
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现在有很多开发成熟的数学方法,
04:31
a lot of preprogrammed tools,
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有很多预编工具,
04:33
including free ones,
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包括很多免费的,
04:35
and an ever-increasing amount
of computational power available to us.
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我们能获取的计算能力在不断增多。
04:40
The power and beauty
of mathematical modeling
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数学建模的力与美
04:44
lies in the fact
that it makes you formalize,
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在于它可以,
04:46
in a very rigorous way,
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用最有力的方式,
04:48
what we think we know.
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将我们的认知形式化。
04:50
We make assumptions,
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我们做出假设,
04:52
translate them into equations,
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把假设翻译成方程,
04:53
run simulations,
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模拟场景,
04:55
all to answer the question:
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全是为了回答一个问题:
04:57
In a world where my assumptions are true,
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如果我的假设正确的话,
04:59
what do I expect to see?
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我能看到什么?
05:01
It's a pretty simple conceptual framework.
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这是一个十分简单的概念框架。
05:04
It's all about asking the right questions.
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全在于问对问题。
05:06
But it can unleash numerous opportunities
for testing biological hypotheses.
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但这会释放出大量
检验生物学假设的机会。
05:11
If our predictions match our observations,
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如果我们的预测与观察相吻合,
05:14
great! -- we got it right,
so we can make further predictions
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太好了!证明我们是对的,
这样我们就能做出进一步的预测,
05:17
by changing this or that
aspect of the model.
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通过改变模型的其他方面。
05:20
If, however, our predictions
do not match our observations,
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但如果,我们的预测
与我们的观察不符,
05:24
that means that some
of our assumptions are wrong,
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这就意味着我们的假设出了错,
05:27
and so our understanding
of the key mechanisms
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意味着我们对于生物学中潜在的,
05:29
of underlying biology
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关键机制
05:30
is still incomplete.
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理解得还不够完善。
05:32
Luckily, since this is a model,
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幸好,因为这只是个模型,
05:35
we control all the assumptions.
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我们能控制所有的假设。
05:37
So we can go through them, one by one,
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所以我们可以一个一个的仔细检查,
05:39
identifying which one or ones
are causing the discrepancy.
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找出是哪个或哪些假设导致了偏差。
05:43
And then we can fill this newly
identified gap in knowledge
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然后我们就能通过实验与理论的方式,
05:47
using both experimental
and theoretical approaches.
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填补新发现的知识空白。
05:50
Of course, any ecosystem
is extremely complex,
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当然,任何生态系统都极其复杂,
05:53
and trying to describe all the moving
parts is not only very difficult,
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尝试去描述这之中的所有运动
不仅十分困难,
05:57
but also not very informative.
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而且也无法获得太多信息。
05:59
There's also the issue of timescales,
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并且还有时间范围的问题,
06:01
because some processes take place
on a scale of seconds, some minutes,
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因为有些过程发生的时间
以秒为单位,有的以分为单位,
06:05
some days, months and years.
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还有的以天、月、年为单位。
06:07
It may not always be possible
to separate those out experimentally.
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把这些全部通过实验分开
是不太可能的。
06:11
And some things happen
so quickly or so slowly
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有的发生的太快,
有的发生的太慢,
06:14
that you may physically
never be able to measure them.
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以至于你不可能去测量它们。
06:17
But as mathematicians,
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但是作为数学家,
06:19
we have the power to zoom in
on any subsystem in any timescale
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我们有能力在任何时间范围内
放大任何子系统,
06:25
and simulate effects of interventions
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并模拟在任何时间范围中,
06:27
that take place in any timescale.
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可能发生的干预效果。
06:31
Of course, this isn't the work
of a modeler alone.
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当然,这项工作光靠建模者是不行的。
06:34
It has to happen in close
collaboration with biologists.
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他们还得与生物学家密切合作才行。
06:38
And it does demand
some capacity of translation
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这确实需要一些翻译能力,
06:41
on both sides.
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双方都需要。
06:43
But starting with a theoretical
formulation of a problem
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但是从一个问题的理论构想开始
06:47
can unleash numerous opportunities
for testing hypotheses
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可以释放出大量的机会
去验证假设
06:50
and simulating scenarios
and therapeutic interventions,
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去模拟场景和治疗干预,
06:54
all in a completely safe way.
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这都是在完全安全的情况下进行的。
06:56
It can identify gaps in knowledge
and logical inconsistencies
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这可以找出知识的空白、
逻辑的不一致,
07:02
and can help guide us
as to where we should keep looking
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可以帮忙引导我们,
让我们知道哪里值得继续寻找,
07:05
and where there may be a dead end.
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哪里可能是个死胡同。
07:07
In other words:
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换句话说:
07:08
mathematical modeling
can help us answer questions
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数学建模能帮助我们回答
07:12
that directly affect people's health --
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那些直接影响人们健康的问题——
07:15
that affect each
person's health, actually --
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实际上,这会影响每个人的健康——
07:18
because mathematical modeling will be key
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因为数学建模,
07:21
to propelling personalized medicine.
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将会是推动个性化医疗的关键。
07:24
And it all comes down
to asking the right question
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而这一切的关键在于问对问题,
07:27
and translating it
to the right equation ...
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然后把它翻译成正确的方程,
07:30
and back.
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再翻译回去。
07:32
Thank you.
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谢谢。
07:33
(Applause)
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(掌声)
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