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Single particle cryo-EM is getting increasingly accessible to researchers from diverse research areas. Furthermore, recent innovations in cryo-EM hardware development and data acquisition strategies have led to an increase in data quality as well as quantity. However, the overall quality of a data set does not directly correlate with the quality of a single image or the number of images collected, but also strongly depends on the sample itself. Nevertheless, with great data comes great responsibility and just having a large data set is not necessarily advantageous. To get the most out of a data collection, the researcher needs to carefully monitor and curate all data, ideally while its still being collected. Therefore, automated data processing and the analysis of the collected data live during acqui- sition becomes increasingly important. To get the most information in the shortest amount of time, ideally, all major pre-processing steps would be executed while the data are still collected. In this way, the researcher gets direct feedback about the sample quality and has the chance to make necessary adjustments to the data collection. While there are several tools available to execute the processing pipeline, they all use a static set of input settings for each individual task, limiting their applicability. In this thesis, I present TranSPHIRE, a tool for fully automated on-the-fly data processing. It executes all the important pre-processing steps required for the processing of single particle projects, as well as filamentous samples, in a parallel manner. I demonstrate the capabilities of the TranSPHIRE pipeline based on three different scenarios: A previously unknown data set; a data set consisting of two sub-populations, where only one is targeted for particle picking; and a filamentous sample. All three scenarios lead to a high-resolution 3D reconstruction of the target protein in a fully automated manner. Therefore, fully automated data processing and optimization could pave the way for high-throughput screenings of unknown samples without user intervention. Additionally, I present sp_meridien_alpha.py, a modification of the single particle 3D refinement program sp_meridien.py, to allow filamentous processing in the SPHIRE package. In summary, the software tool TranSPHIRE and the filamentous 3D refinement program sp_meri- dien_alpha.py combined simplify the cryo-EM data collection and processing and thereby present a valuable contribution to the field.