Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning
algorithms for medium-scale supervised and unsupervised problems. This package focuses
on bringing machine learning to non-specialists using a general-purpose high-level …

Synthetic biologists engineer complex artificial biological systems to investigate natural
biological phenomena and for a variety of applications. We outline the basic features of
synthetic biology as a new engineering discipline, covering examples from the latest …

Synthetic biology is a research field that combines the investigative nature of biology with
the constructive nature of engineering. Efforts in synthetic biology have largely focused on
the creation and perfection of genetic devices and small modules that are constructed from …

Pattern formation is a hallmark of coordinated cell behaviour in both single and multicellular
organisms 1, 2, 3. It typically involves cell–cell communication and intracellular signal
processing. Here we show a synthetic multicellular system in which genetically engineered …

De novo engineering of gene circuits inside cells is extremely difficult 1, 2, 3, 4, 5, 6, 7, 8, 9,
and efforts to realize predictable and robust performance must deal with noise in gene
expression and variation in phenotypes between cells 10, 11, 12. Here we demonstrate that …

The precise nature of information flow through a biological network, which is governed by
factors such as response sensitivities and noise propagation, greatly affects the operation of
biological systems. Quantitative analysis of these properties is often difficult in naturally …

Engineered biological systems that integrate multi-input sensing, sophisticated information
processing, and precisely regulated actuation in living cells could be useful in a variety of
applications. For example, anticancer therapies could be engineered to detect and respond …

One of the important challenges in the emerging field of synthetic biology is designing
artificial networks that achieve coordinated behavior in cell communities. Here we present a
synthetic multicellular bacterial system where receiver cells exhibit transient gene …

Abstract Molecular automata 1, 2, 3 that combine sensing 4, 5, 6, computation 7, 8, 9, 10, 11,
12 and actuation 13, 14 enable programmable manipulation of biological systems. We use
RNA interference (RNAi) 15 in human kidney cells to construct a molecular computing core …

The construction of artificial networks of transcriptional control elements in living cells
represents a new frontier for biological engineering. However, biological circuit engineers
will have to confront their inability to predict the precise behavior of even the most simple …