Automatic Particle Picking of Biological Molecules Imaged by Electron Microscopy

نویسندگان

  • Jasmine Banks
  • Rosalba Rothnagel
  • Ben Hankamer
چکیده

One of the next great challenges of cell biology is the determination of the enormous number of protein structures encoded in genomes. In recent years, advances in electron cryo-microscopy and high-resolution single particle analysis have developed to the point where they now provide a methodology for high resolution structure determination. Using this approach, images of randomly oriented single particles are aligned computationally to reconstruct 3-D structures of proteins and even whole viruses. One of the limiting factors in obtaining highresolution reconstructions is obtaining a large enough representative dataset ( 100 000 particles). Traditionally particles have been manually picked which is an extremely labour intensive process. The problem is made especially difficult by the low signal-to-noise ratio of the images. This paper describes the development of automatic particle picking software, which has been tested with both negatively stained and cryo-electron micrographs. This algorithm has been shown to be capable of selecting most of the particles, with few false positives. Further work will involve extending the software to detect differently shaped and oriented particles.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Particle quality assessment and sorting for automatic and semiautomatic particle-picking techniques.

Three-dimensional reconstruction of biological specimens using electron microscopy by single particle methodologies requires the identification and extraction of the imaged particles from the acquired micrographs. Automatic and semiautomatic particle selection approaches can localize these particles, minimizing the user interaction, but at the cost of selecting a non-negligible number of incorr...

متن کامل

Automatic post-picking using MAPPOS improves particle image detection from Cryo-EM micrographs

Cryo-electron microscopy (cryo-EM) studies using single particle reconstruction are extensively used to reveal structural information on macromolecular complexes. Aiming at the highest achievable resolution, state of the art electron microscopes automatically acquire thousands of high-quality micrographs. Particles are detected on and boxed out from each micrograph using fully- or semi-automate...

متن کامل

APPLE Picker: Automatic Particle Picking, a Low-Effort Cryo-EM Framework

Particle picking is a crucial first step in the computational pipeline of single-particle cryo-electron microscopy (cryo-EM). Selecting particles from the micrographs is difficult especially for small particles with low contrast. As high-resolution reconstruction typically requires hundreds of thousands of particles, manually picking that many particles is often too time-consuming. While semi-a...

متن کامل

Automatic particle selection from electron micrographs using machine learning techniques.

The 3D reconstruction of biological specimens using Electron Microscopy is currently capable of achieving subnanometer resolution. Unfortunately, this goal requires gathering tens of thousands of projection images that are frequently selected manually from micrographs. In this paper we introduce a new automatic particle selection that learns from the user which particles are of interest. The tr...

متن کامل

Single-particle selection and alignment with heavy atom cluster-antibody conjugates (Nanogoldysingle-chain Fv antibody fragmentsycryoelectron microscopyyimage processingythree-dimensional reconstruction)

A method is proposed for selecting and aligning images of single biological particles to obtain highresolution structural information by cryoelectron microscopy. The particles will be labeled with multiple heavy atom clusters to permit the precise determination of particle locations and relative orientations even when imaged close to focus with a low electron dose, conditions optimal for record...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2003