Ariadne: Analysis for Machine Learning Program

Machine learning has transformed domains like vision and translation, and is now increasingly used in science, where the correctness of such code is vital. Python is popular for machine learning, in part because of its wealth of machine learning libraries, and is felt to make development faster; however, this dynamic language has less support for error detection at code creation time than tools like Eclipse. This is especially problematic for machine learning: given its statistical nature, code with subtle errors may run and produce results that look plausible but are meaningless. This can vitiate scientific results. We report on Ariadne: applying a static framework, WALA, to machine learning code that uses TensorFlow. We have created static analysis for Python, a type system for tracking tensors---Tensorflow's core data structures---and a data flow analysis to track their usage. We report on how it was built and present some early results

Investigating energy-based pool structure selection in the structure ensemble modeling with experimental distance constraints : the example from a multidomain protein Pub1

The structural variations of multidomain proteins with flexible parts mediate many biological processes, and a structure ensemble can be determined by selecting a weighted combination of representative structures from a simulated structure pool, producing the best fit to experimental constraints such as interatomic distance. In this study, a hybrid structure‐based and physics‐based atomistic force field with an efficient sampling strategy is adopted to simulate a model di‐domain protein against experimental paramagnetic relaxation enhancement (PRE) data that correspond to distance constraints. The molecular dynamics simulations produce a wide range of conformations depicted on a protein energy landscape. Subsequently, a conformational ensemble recovered with low‐energy structures and the minimum‐size restraint is identified in good agreement with experimental PRE rates, and the result is also supported by chemical shift perturbations and small‐angle X‐ray scattering data. It is illustrated that the regularizations of energy and ensemble‐size prevent an arbitrary interpretation of protein conformations. Moreover, energy is found to serve as a critical control to refine the structure pool and prevent data overfitting, because the absence of energy regularization exposes ensemble construction to the noise from high‐energy structures and causes a more ambiguous representation of protein conformations. Finally, we perform structure‐ensemble optimizations with a topology‐based structure pool, to enhance the understanding on the ensemble results from different sources of pool candidates.MOE (Min. of Education, S’pore)Accepted versio

Diversifying the use of tuna to improve food security and public health in Pacific Island countries and territories

The large tuna resources of the Western and Central Pacific Ocean are delivering great economic benefits to Pacific Island countries and territories (PICTs) through sale of licences to distant water fishing nations and employment in fish processing. However, tuna needs to contribute to Pacific Island societies in another important way-by increasing local access to the fish required for good nutrition to help combat the worldand#039;s highest levels of diabetes and obesity. Analyses reported here demonstrate that coastal fisheries in 16 of the 22 PICTs will not provide the fish recommended for good nutrition of growing Pacific Island populations, and that by 2020 tuna will need to supply 12% of the fish required by PICTs for food security, increasing to 25% by 2035. In relative terms, the percentages of the regionand#039;s tuna catch that will be needed in 2020 and 2035 to fill the gap in domestic fish supply are small, i.e., 2.1% and 5.9% of the average present-day industrial catch, respectively. Interventions based on expanding the use of nearshore fish aggregating devices (FADs) to assist small-scale fishers catch tuna, distributing small tuna and bycatch offloaded by industrial fleets at regional ports, and improving access to canned tuna for inland populations, promise to increase access to fish for sustaining the health of the regionand#039;s growing populations. The actions, research and policies required to implement these interventions effectively, and the investments needed to maintain the stocks underpinning the considerable socio-economic benefits that flow from tuna, are described