Channel estimation for millimeter-wave (mmWave) massive MIMO with hybrid precoding is challenging, since the number of radio frequency (RF) chains is usually much smaller than that of antennas. To date, several channel estimation schemes have been proposed for mmWave massive MIMO over narrowband channels, while practical mmWave channels exhibit the frequency-selective fading (FSF). To this end, this letter proposes a multi-user uplink channel estimation scheme for mmWave massive MIMO over FSF channels. Specifically, by exploiting the angle-domain structured sparsity of mmWave FSF channels, a distributed compressive sensing (DCS)-based channel estimation scheme is proposed. Moreover, by using the grid matching pursuit strategy with adaptive measurement matrix, the proposed algorithm can solve the power leakage problem caused by the continuous angles of arrival or departure (AoA/AoD). Simulation results verify that the good performance of the proposed solution.Index Terms-Millimeter-wave massive MIMO, frequencyselective fading, channel estimation, compressive sensing.

Transcription factors (TFs) are proteins that bind to specific DNA sequences, thereby playing crucial roles in gene-expression regulation through controlling the transcription of genetic information from DNA to RNA. Transcription cofactors and chromatin remodeling factors are also essential in the gene transcriptional regulation. Identifying and annotating all the TFs are primary and crucial steps for illustrating their functions and understanding the transcriptional regulation. In this study, based on manual literature reviews, we collected and curated 72 TF families for animals, which is currently the most complete list of TF families in animals. Then, we systematically characterized all the TFs in 50 animal species and constructed a comprehensive animal TF database, AnimalTFDB. To better serve the community, we provided detailed annotations for each TF, including basic information, gene structure, functional domain, 3D structure hit, Gene Ontology, pathway, protein–protein interaction, paralogs, orthologs, potential TF-binding sites and targets. In addition, we collected and annotated transcription cofactors and chromatin remodeling factors. AnimalTFDB has a user-friendly web interface with multiple browse and search functions, as well as data downloading. It is freely available at http://www.bioguo.org/AnimalTFDB/.

Summary An individual’s sex has been long recognized as a key factor affecting cancer incidence, prognosis and treatment responses. However, the molecular basis for sex disparities in cancer remains poorly understood. We performed a comprehensive analysis of molecular differences between male and female patients in 13 cancer types of The Cancer Genome Atlas and revealed two sex-effect groups associated with distinct incidence and mortality profiles. One group contains a small number of sex-affected genes, whereas the other shows much more extensive sex-biased molecular signatures. Importantly, 53% of clinically actionable genes (60/114) show sex-biased signatures. Our study provides a systematic molecular-level understanding of sex effects in diverse cancers and suggests a pressing need to develop sex-specific therapeutic strategies in certain cancer types.

Tumor hypoxia is a major contributor to resistance to anti-cancer therapies. Given that the results of hypoxia-targeted therapy trials have been disappointing, a more personalized approach may be needed. Here we characterize multi-OMIC molecular features associated with tumor hypoxia and identify molecular alterations that correlate with both drug-resistant and drug-sensitive responses to anti-cancer drugs. Based on a well-established hypoxia gene expression signature, we classify about 10,000 tumor samples into hypoxia score-high and score-low groups across different cancer types from The Cancer Genome Atlas and demonstrate their prognostic associations. We then identify various types of molecular features associated with hypoxia status that correlate with drug resistance but, in some cases, also with drug sensitivity, contrasting the conventional view that hypoxia confers drug resistance. We further show that 110 out of 121 (90.9%) clinically actionable genes can be affected by hypoxia status and experimentally validate the predicted effects of hypoxia on the response to several drugs in cultured cells. Our study provides a comprehensive molecular-level understanding of tumor hypoxia and may have practical implications for clinical cancer therapy.