Wednesday, 30 December 2015

How to count synapses with machine learning

Once upon a time, the Bipolar Chemist was formerly known as the Bipolar Statistician. His primary interests were in statistical modelling of time series data (ARCH/GARCH), as well as count statistics using the discrete Poisson probability distribution, among others. The moment the Bipolar Chemist heard about this great new discovery from the hallowed halls of Carnegie Mellon University, he immediately sent word to its discoverers requesting a possible pipeline collaboration. Modelling such rich and exciting data would be a dream come true for the Bipolar Chemist/Statistician.

Synaptic density analysis using a new machine-learning algorithm
Image credit: Saket Navlakha and Alison Barth; Journal of Neuroscience.

This image shows synapses in the somatosensory cortex stained with ethanolic phosphotungstic acid and visualised using electron microscopy. Synapses were identified using a Carnegie Mellon-developed machine learning algorithm that enables a high-throughput analysis of experience-dependent changes in synapse properties across the cortical column. For this image, candidate synapses were selected from electron micrographs and aligned, then pseudocoloured for contrast. Researchers are now beginning to use this data to develop new hypotheses about how synapses are organised in the neocortex in response to sensory input. 
This research is the latest example of how researchers with the Carnegie Mellon's BrainHub initiative are combining their expertise in biology and computer science to create new tools to advance neuroscience. The technique uses a special chemical preparation that deeply stains the synapses in a sample of brain tissue. When the tissue is imaged using an electron microscope, only the synapses can be seen, creating an image that can easily be classified by a computer program. Researchers then use machine learning algorithms to identify an compare synapse properties across a column of the cerebral cortex.

Image credit: Howard Lam, University of Sydney

Tuesday, 29 December 2015

The Bipolar Chemist and Zing Conferences

The Bipolar Chemist has just registered for the following scientific conferences in the US and Ireland in 2016. He is hoping to meet like-minded computational chemists, biophysicists, biostatisticians and neuroscientists to gain further knowledge and insight into bipolar disorder, particularly in relation to:
  • cAMP signal transduction
  • GPCR modelling and simulation
  • Voltage-gated ion channels and transporters
  • Optogenetics of photoactivatable adenylate cyclases (pACs)
  • Whole-cell computational approaches to synthetic biology
  • Neuropsychopharmacology and cognitive neuroepigenetics
  • Fractal symmetry of protein interior and exterior
  • Clifford algebra and DNA structure
Mad Poster Scramble at the Molecular Modelling 2015 conference @ UNSW 

Structure-Based Drug Design: 21st - 24th February 2016
Structure-based drug design (SBDD) has evolved a great deal over the past 30 years since the concept of the "Lock and Key" hypothesis was first reduced to practice in the HIV-1 protease field, leading to the rational design of a number of molecules that are at the forefront of effective therapy. Evolution of techniques such x-ray crystallography, NMR and computational chemistry have enabled a more informed understanding of binding events, encouraging many groups to employ SBDD strategies to wide range of drug-relevant targets.
Zing's inaugural SBDD event will showcase many of the advances made in structural biology, fragment-based methodologies and computational chemistry, demonstrating how these have been used to enable drug discovery programs in a range of drug target classes from enzymes, to more complex G-protein coupled receptors (GPCRs) and protein-protein interactions (PPIs). The conference will also feature some of the emerging technologies in the field, which will serve as a glimpse into the future of drug discovery as SBDD becomes more diverse and unrestrained.
You will enjoy the opportunity to engage with many of the pace-setters in the SBDD field, leaving with fresh ideas and concepts that will help to continue to build success in your drug discovery efforts.

Structure-based drug design @ Santa Rosa, California

Propagation in Neurodegenerative Disease: 8th - 11th August 2016

Neurodegenerative diseases are characterised by the progressive decline of neuronal functions in a spatiotemporal fashion, leading to the worsening of neurological symptoms, in some cases, with devastating speed. This is accompanied by gradual intensity of neuropathological findings from more to less affected regions in the nervous system. The molecular pathway driving progressive decline of disease symptoms and pathology is not yet understood. However, the amplification of pathological protein assemblies, which spread from cell-to-cell, may well explain these phenomena. We will bring together neurologists, neuropathologists and basic scientists from a wide variety of neurodegenerative diseases to discuss the implications of these mechanisms for building disease models and therapeutic strategies. We will also discuss the similarities and differences between the different classes of neurodegeneration, comparing to prototypical prion diseases. Lastly, we will examine the role of inflammation and cellular stress in potentiating the initiation and spreading of pathology.

Propagation in neurodenerative disease @ Dublin, Ireland

Nucleic Acids: 2nd - 5th December 2016
Nucleic acids are the cell's informational macromolecules. DNA is a repository of genetic information and must accurately copied once and only once in each cell cycle. Its integrity is vital to the cell, and it is the only molecule that is repaired if damage occurs. DNA undergoes a recombination that creates diversity and leads to evolution, yet also provides an important method of repair. In eukaryotic cells DNA is packaged into chromosomes in a way that allows it to be packed into the cell nucleus, yet accessible to the cell's machinery for reading out its genetic information. By contrast RNA is the 'working substance' of genetics and an extremely versatile molecule. Of course it is the messenger that passes the information between DNA and protein synthesis, yet it does so much more. It is the key component of the ribosome, as well as the tRNA species involved in translation. RNA can act as a molecular switch responding to small molecules in order control gene expression, and can also accelerate chemical reactions by a million fold or more in the manner of an enzyme. Increasingly we realise that RNA is also involved in critical and complex regulatory processes.

Nucleic acids @ Tampa, Florida

Bipolar Disorder and Adenylate Cyclase 2: A Fairy Tale

Once upon a time, in a land far, far away, there lived a complex mental illness whose name was Bipolar Disorder. Affecting about two percent of the population, the illness is characterised by extreme “mood swings” that cycle between episodes of mania, hypomania and depression. Then on one fateful day, the Bipolar Chemist entered this faraway land, armed with many magical methods, namely homology modelling, molecular dynamics and site-directed mutagenesis, to name but a few. He was very keen to work his magic on a particular transmembrane protein called adenylate cylase 2, an enzyme implicated as a risk factor in a recent genome-wide association study (GWAS). After receiving a prestigious School of Science and Technology Special Project award from the University of New England in 2013, the Bipolar Chemist’s lifelong dream of learning molecular modelling and simulation finally became a reality via a four-week research traineeship. With the help and support of his beloved supervisor, he worked day and night on the Swing The Mood project, examining the protein-structure relationships of adenylate cyclase 2 with respect to cyclic adenosine monophosphate (cAMP) signal transduction, a key biological pathway involved in the development of bipolar disorder. Fast-forward one year to today and alas, the Bipolar Chemist’s first ever poster is here to stay! And they all lived happily ever after…